Research on Capacity Addition using Market Model with Transmission Congestion under Competitive Environment

NASA Astrophysics Data System (ADS)

Katsura, Yasufumi; Attaviriyanupap, Pathom; Kataoka, Yoshihiko

In this research, the fundamental premises for deregulation of the electric power industry are reevaluated. The authors develop a simple model to represent wholesale electricity market with highly congested network. The model is developed by simplifying the power system and market in New York ISO based on available data of New York ISO in 2004 with some estimation. Based on the developed model and construction cost data from the past, the economic impact of transmission line addition on market participants and the impact of deregulation on power plant additions under market with transmission congestion are studied. Simulation results show that the market signals may fail to facilitate proper capacity additions and results in the undesirable over-construction and insufficient-construction cycle of capacity addition.

3D model of filler melting with micro-beam plasma arc based on additive manufacturing technology

NASA Astrophysics Data System (ADS)

Chen, Weilin; Yang, Tao; Yang, Ruixin

2017-07-01

Additive manufacturing technology is a systematic process based on discrete-accumulation principle, which is derived by the dimension of parts. Aiming at the dimension mathematical model and slicing problems in additive manufacturing process, the constitutive relations between micro-beam plasma welding parameters and the dimension of part were investigated. The slicing algorithm and slicing were also studied based on the dimension characteristics. By using the direct slicing algorithm according to the geometric characteristics of model, a hollow thin-wall spherical part was fabricated by 3D additive manufacturing technology using micro-beam plasma.

Analysis of economics of a TV broadcasting satellite for additional nationwide TV programs

NASA Technical Reports Server (NTRS)

Becker, D.; Mertens, G.; Rappold, A.; Seith, W.

1977-01-01

The influence of a TV broadcasting satellite, transmitting four additional TV networks was analyzed. It is assumed that the cost of the satellite systems will be financed by the cable TV system operators. The additional TV programs increase income by attracting additional subscribers. Two economic models were established: (1) each local network is regarded as an independent economic unit with individual fees (cost price model) and (2) all networks are part of one public cable TV company with uniform fees (uniform price model). Assumptions are made for penetration as a function of subscription rates. Main results of the study are: the installation of a TV broadcasting satellite improves the economics of CTV-networks in both models; the overall coverage achievable by the uniform price model is significantly higher than that achievable by the cost price model.

Using generalized additive (mixed) models to analyze single case designs.

PubMed

Shadish, William R; Zuur, Alain F; Sullivan, Kristynn J

2014-04-01

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

A novel model for through-silicon via (TSV) filling process simulation considering three additives and current density effect

NASA Astrophysics Data System (ADS)

Wang, Fuliang; Zhao, Zhipeng; Wang, Feng; Wang, Yan; Nie, Nantian

2017-12-01

Through-silicon via (TSV) filling by electrochemical deposition is still a challenge for 3D IC packaging, and three-component additive systems (accelerator, suppressor, and leveler) were commonly used in the industry to achieve void-free filling. However, models considering three additive systems and the current density effect have not been fully studied. In this paper, a novel three-component model was developed to study the TSV filling mechanism and process, where the interaction behavior of the three additives (accelerator, suppressor, and leveler) were considered, and the adsorption, desorption, and consumption coefficient of the three additives were changed with the current density. Based on this new model, the three filling types (seam void, ‘V’ shape, and key hole) were simulated under different current density conditions, and the filling results were verified by experiments. The effect of the current density on the copper ion concentration, additives surface coverage, and local current density distribution during the TSV filling process were obtained. Based on the simulation and experimental results, the diffusion-adsorption-desorption-consumption competition behavior between the suppressor, the accelerator, and the leveler were discussed. The filling mechanisms under different current densities were also analyzed.

Conservative Exposure Predictions for Rapid Risk Assessment of Phase-Separated Additives in Medical Device Polymers.

PubMed

Chandrasekar, Vaishnavi; Janes, Dustin W; Saylor, David M; Hood, Alan; Bajaj, Akhil; Duncan, Timothy V; Zheng, Jiwen; Isayeva, Irada S; Forrey, Christopher; Casey, Brendan J

2018-01-01

A novel approach for rapid risk assessment of targeted leachables in medical device polymers is proposed and validated. Risk evaluation involves understanding the potential of these additives to migrate out of the polymer, and comparing their exposure to a toxicological threshold value. In this study, we propose that a simple diffusive transport model can be used to provide conservative exposure estimates for phase separated color additives in device polymers. This model has been illustrated using a representative phthalocyanine color additive (manganese phthalocyanine, MnPC) and polymer (PEBAX 2533) system. Sorption experiments of MnPC into PEBAX were conducted in order to experimentally determine the diffusion coefficient, D = (1.6 ± 0.5) × 10 -11  cm 2 /s, and matrix solubility limit, C s  = 0.089 wt.%, and model predicted exposure values were validated by extraction experiments. Exposure values for the color additive were compared to a toxicological threshold for a sample risk assessment. Results from this study indicate that a diffusion model-based approach to predict exposure has considerable potential for use as a rapid, screening-level tool to assess the risk of color additives and other small molecule additives in medical device polymers.

The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing

PubMed Central

Rijkhorst, Erik-Jan; Hofman, Mark; Forouzanfar, Tymour; Wolff, Jan

2016-01-01

Objectives: Additively manufactured bone models, implants and drill guides are becoming increasingly popular amongst maxillofacial surgeons and dentists. To date, such constructs are commonly manufactured using CT technology that induces ionizing radiation. Recently, ultrashort echo time (UTE) MRI sequences have been developed that allow radiation-free imaging of facial bones. The aim of the present study was to assess the feasibility of UTE MRI sequences for medical additive manufacturing (AM). Methods: Three morphologically different dry human mandibles were scanned using a CT and MRI scanner. Additionally, optical scans of all three mandibles were made to acquire a “gold standard”. All CT and MRI scans were converted into Standard Tessellation Language (STL) models and geometrically compared with the gold standard. To quantify the accuracy of the AM process, the CT, MRI and gold-standard STL models of one of the mandibles were additively manufactured, optically scanned and compared with the original gold-standard STL model. Results: Geometric differences between all three CT-derived STL models and the gold standard were <1.0 mm. All three MRI-derived STL models generally presented deviations <1.5 mm in the symphyseal and mandibular area. The AM process introduced minor deviations of <0.5 mm. Conclusions: This study demonstrates that MRI using UTE sequences is a feasible alternative to CT in generating STL models of the mandible and would therefore be suitable for surgical planning and AM. Further in vivo studies are necessary to assess the usability of UTE MRI sequences in clinical settings. PMID:26943179

Study of abrasive resistance of foundries models obtained with use of additive technology

NASA Astrophysics Data System (ADS)

Ol'khovik, Evgeniy

2017-10-01

A problem of determination of resistance of the foundry models and patterns from ABS (PLA) plastic, obtained by the method of 3D printing with using FDM additive technology, to abrasive wear and resistance in the environment of foundry sand mould is considered in the present study. The description of a technique and equipment for tests of castings models and patterns for wear is provided in the article. The manufacturing techniques of models with the use of the 3D printer (additive technology) are described. The scheme with vibration load was applied to samples tests. For the most qualitative research of influence of sandy mix on plastic, models in real conditions of abrasive wear have been organized. The results also examined the application of acrylic paintwork to the plastic model and a two-component coating. The practical offers and recommendation on production of master models with the use of FDM technology allowing one to reach indicators of durability, exceeding 2000 cycles of moulding in foundry sand mix, are described.

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models.

PubMed

Nagai, Takashi

2017-10-01

The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630. © 2017 SETAC. © 2017 SETAC.

Large Eddy Simulation Study for Fluid Disintegration and Mixing

NASA Technical Reports Server (NTRS)

Bellan, Josette; Taskinoglu, Ezgi

2011-01-01

A new modeling approach is based on the concept of large eddy simulation (LES) within which the large scales are computed and the small scales are modeled. The new approach is expected to retain the fidelity of the physics while also being computationally efficient. Typically, only models for the small-scale fluxes of momentum, species, and enthalpy are used to reintroduce in the simulation the physics lost because the computation only resolves the large scales. These models are called subgrid (SGS) models because they operate at a scale smaller than the LES grid. In a previous study of thermodynamically supercritical fluid disintegration and mixing, additional small-scale terms, one in the momentum and one in the energy conservation equations, were identified as requiring modeling. These additional terms were due to the tight coupling between dynamics and real-gas thermodynamics. It was inferred that if these terms would not be modeled, the high density-gradient magnitude regions, experimentally identified as a characteristic feature of these flows, would not be accurately predicted without the additional term in the momentum equation; these high density-gradient magnitude regions were experimentally shown to redistribute turbulence in the flow. And it was also inferred that without the additional term in the energy equation, the heat flux magnitude could not be accurately predicted; the heat flux to the wall of combustion devices is a crucial quantity that determined necessary wall material properties. The present work involves situations where only the term in the momentum equation is important. Without this additional term in the momentum equation, neither the SGS-flux constant-coefficient Smagorinsky model nor the SGS-flux constant-coefficient Gradient model could reproduce in LES the pressure field or the high density-gradient magnitude regions; the SGS-flux constant- coefficient Scale-Similarity model was the most successful in this endeavor although not totally satisfactory. With a model for the additional term in the momentum equation, the predictions of the constant-coefficient Smagorinsky and constant-coefficient Scale-Similarity models were improved to a certain extent; however, most of the improvement was obtained for the Gradient model. The previously derived model and a newly developed model for the additional term in the momentum equation were both tested, with the new model proving even more successful than the previous model at reproducing the high density-gradient magnitude regions. Several dynamic SGS-flux models, in which the SGS-flux model coefficient is computed as part of the simulation, were tested in conjunction with the new model for this additional term in the momentum equation. The most successful dynamic model was a "mixed" model combining the Smagorinsky and Gradient models. This work is directly applicable to simulations of gas turbine engines (aeronautics) and rocket engines (astronautics).

Representational Flexibility and Problem-Solving Ability in Fraction and Decimal Number Addition: A Structural Model

ERIC Educational Resources Information Center

Deliyianni, Eleni; Gagatsis, Athanasios; Elia, Iliada; Panaoura, Areti

2016-01-01

The aim of this study was to propose and validate a structural model in fraction and decimal number addition, which is founded primarily on a synthesis of major theoretical approaches in the field of representations in Mathematics and also on previous research on the learning of fractions and decimals. The study was conducted among 1,701 primary…

Atomistic modeling and simulation of the role of Be and Bi in Al diffusion in U-Mo fuel

NASA Astrophysics Data System (ADS)

Hofman, G. L.; Bozzolo, G.; Mosca, H. O.; Yacout, A. M.

2011-07-01

Within the RERTR program, previous experimental and modeling studies identified Si as the alloying addition to the Al cladding responsible for inhibiting Al interdiffusion in the UMo fuel. However, difficulties with reprocessing have rendered this choice inappropriate, leading to the need to study alternative elements. In this work, we discuss the results of an atomistic modeling effort which allows for the systematic study of several possible alloying additions. Based on the behavior observed in the phase diagrams, beryllium or bismuth additions suggest themselves as possible options to replace Si. The results of temperature-dependent simulations using the Bozzolo-Ferrante-Smith (BFS) method for the energetics for varying concentrations of either element are shown, indicating that Be could have a substantial effect in stopping Al interdiffusion, while Bi does not. Details of the calculations and the dependence of the role of each alloying addition as a function of temperature and concentration (of beryllium or bismuth in Al) are shown.

Applying Emax model and bivariate thin plate splines to assess drug interactions

PubMed Central

Kong, Maiying; Lee, J. Jack

2014-01-01

We review the semiparametric approach previously proposed by Kong and Lee and extend it to a case in which the dose-effect curves follow the Emax model instead of the median effect equation. When the maximum effects for the investigated drugs are different, we provide a procedure to obtain the additive effect based on the Loewe additivity model. Then, we apply a bivariate thin plate spline approach to estimate the effect beyond additivity along with its 95% point-wise confidence interval as well as its 95% simultaneous confidence interval for any combination dose. Thus, synergy, additivity, and antagonism can be identified. The advantages of the method are that it provides an overall assessment of the combination effect on the entire two-dimensional dose space spanned by the experimental doses, and it enables us to identify complex patterns of drug interaction in combination studies. In addition, this approach is robust to outliers. To illustrate this procedure, we analyzed data from two case studies. PMID:20036878

Applying Emax model and bivariate thin plate splines to assess drug interactions.

PubMed

Kong, Maiying; Lee, J Jack

2010-01-01

We review the semiparametric approach previously proposed by Kong and Lee and extend it to a case in which the dose-effect curves follow the Emax model instead of the median effect equation. When the maximum effects for the investigated drugs are different, we provide a procedure to obtain the additive effect based on the Loewe additivity model. Then, we apply a bivariate thin plate spline approach to estimate the effect beyond additivity along with its 95 per cent point-wise confidence interval as well as its 95 per cent simultaneous confidence interval for any combination dose. Thus, synergy, additivity, and antagonism can be identified. The advantages of the method are that it provides an overall assessment of the combination effect on the entire two-dimensional dose space spanned by the experimental doses, and it enables us to identify complex patterns of drug interaction in combination studies. In addition, this approach is robust to outliers. To illustrate this procedure, we analyzed data from two case studies.

Potential uncertainty reduction in model-averaged benchmark dose estimates informed by an additional dose study.

PubMed

Shao, Kan; Small, Mitchell J

2011-10-01

A methodology is presented for assessing the information value of an additional dosage experiment in existing bioassay studies. The analysis demonstrates the potential reduction in the uncertainty of toxicity metrics derived from expanded studies, providing insights for future studies. Bayesian methods are used to fit alternative dose-response models using Markov chain Monte Carlo (MCMC) simulation for parameter estimation and Bayesian model averaging (BMA) is used to compare and combine the alternative models. BMA predictions for benchmark dose (BMD) are developed, with uncertainty in these predictions used to derive the lower bound BMDL. The MCMC and BMA results provide a basis for a subsequent Monte Carlo analysis that backcasts the dosage where an additional test group would have been most beneficial in reducing the uncertainty in the BMD prediction, along with the magnitude of the expected uncertainty reduction. Uncertainty reductions are measured in terms of reduced interval widths of predicted BMD values and increases in BMDL values that occur as a result of this reduced uncertainty. The methodology is illustrated using two existing data sets for TCDD carcinogenicity, fitted with two alternative dose-response models (logistic and quantal-linear). The example shows that an additional dose at a relatively high value would have been most effective for reducing the uncertainty in BMA BMD estimates, with predicted reductions in the widths of uncertainty intervals of approximately 30%, and expected increases in BMDL values of 5-10%. The results demonstrate that dose selection for studies that subsequently inform dose-response models can benefit from consideration of how these models will be fit, combined, and interpreted. © 2011 Society for Risk Analysis.

Response to Selection in Finite Locus Models with Nonadditive Effects.

PubMed

Esfandyari, Hadi; Henryon, Mark; Berg, Peer; Thomasen, Jørn Rind; Bijma, Piter; Sørensen, Anders Christian

2017-05-01

Under the finite-locus model in the absence of mutation, the additive genetic variation is expected to decrease when directional selection is acting on a population, according to quantitative-genetic theory. However, some theoretical studies of selection suggest that the level of additive variance can be sustained or even increased when nonadditive genetic effects are present. We tested the hypothesis that finite-locus models with both additive and nonadditive genetic effects maintain more additive genetic variance (VA) and realize larger medium- to long-term genetic gains than models with only additive effects when the trait under selection is subject to truncation selection. Four genetic models that included additive, dominance, and additive-by-additive epistatic effects were simulated. The simulated genome for individuals consisted of 25 chromosomes, each with a length of 1 M. One hundred bi-allelic QTL, 4 on each chromosome, were considered. In each generation, 100 sires and 100 dams were mated, producing 5 progeny per mating. The population was selected for a single trait (h2 = 0.1) for 100 discrete generations with selection on phenotype or BLUP-EBV. VA decreased with directional truncation selection even in presence of nonadditive genetic effects. Nonadditive effects influenced long-term response to selection and among genetic models additive gene action had highest response to selection. In addition, in all genetic models, BLUP-EBV resulted in a greater fixation of favorable and unfavorable alleles and higher response than phenotypic selection. In conclusion, for the schemes we simulated, the presence of nonadditive genetic effects had little effect in changes of additive variance and VA decreased by directional selection. © The American Genetic Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A confirmatory factor analysis of the Impact of Event Scale using a sample of World War II and Korean War veterans.

PubMed

Shevlin, M; Hunt, N; Robbins, I

2000-12-01

This study assessed the factor structure of the Impact of Event Scale (IES), a measure of intrusion and avoidance, using a sample of World War II and Korean War veterans who had experienced combat 40-50 years earlier. A series of 3 confirmatory factor analytic models were specified and estimated using LISREL 8.3. Model 1 specified a 1-factor model. Model 2 specified a correlated 2-factor model. Model 3 specified a 2-factor model with additional cross-factor loadings for Items 2 and 12. Model 3 was found to fit the data. In addition, this model was found to be a better explanation of the data than the other models. Also in addition, the correlations between the Intrusion and Avoidance factors and the 4 subscales of the 28-item General Health Questionnaire were examined to determine the distinctiveness of the two IES factors.

Additive Manufacturing (AM) in Expeditionary Operations: Current Needs, Technical Challenges, and Opportunities

DTIC Science & Technology

2016-06-01

site customization of existing models. The author performed an empirical study centered around a survey of United States Marine Corps (USMC) and United...recommends that more studies be performed to determine the best way forward for AM within the USMC and USN. 14. SUBJECT TERMS 3D printing, additive...customization of existing models. The author performed an em- pirical study centered around a survey of United States Marine Corps (USMC) and United

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data

PubMed Central

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2012-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions. PMID:23645976

Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.

PubMed

Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

2013-01-01

Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.

Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance.

PubMed

Bernardo, R

1996-11-01

Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.

Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action

PubMed Central

2013-01-01

Background Genomic selection is an appealing method to select purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation. Results When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives, because in general, the advantage becomes important only after five or six generations post-training. Conclusion Under dominance and without retraining, genomic selection based on the dominance model is superior to the additive model and the breed-specific allele model to maximize crossbred performance through purebred selection. PMID:23621868

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide.

PubMed

Qin, Li-Tang; Chen, Yu-Han; Zhang, Xin; Mo, Ling-Yun; Zeng, Hong-Hu; Liang, Yan-Peng

2018-05-01

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC 50 ) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Applying Additive Hazards Models for Analyzing Survival in Patients with Colorectal Cancer in Fars Province, Southern Iran

PubMed

Madadizadeh, Farzan; Ghanbarnejad, Amin; Ghavami, Vahid; Zare Bandamiri, Mohammad; Mohammadianpanah, Mohammad

2017-04-01

Introduction: Colorectal cancer (CRC) is a commonly fatal cancer that ranks as third worldwide and third and the fifth in Iranian women and men, respectively. There are several methods for analyzing time to event data. Additive hazards regression models take priority over the popular Cox proportional hazards model if the absolute hazard (risk) change instead of hazard ratio is of primary concern, or a proportionality assumption is not made. Methods: This study used data gathered from medical records of 561 colorectal cancer patients who were admitted to Namazi Hospital, Shiraz, Iran, during 2005 to 2010 and followed until December 2015. The nonparametric Aalen’s additive hazards model, semiparametric Lin and Ying’s additive hazards model and Cox proportional hazards model were applied for data analysis. The proportionality assumption for the Cox model was evaluated with a test based on the Schoenfeld residuals and for test goodness of fit in additive models, Cox-Snell residual plots were used. Analyses were performed with SAS 9.2 and R3.2 software. Results: The median follow-up time was 49 months. The five-year survival rate and the mean survival time after cancer diagnosis were 59.6% and 68.1±1.4 months, respectively. Multivariate analyses using Lin and Ying’s additive model and the Cox proportional model indicated that the age of diagnosis, site of tumor, stage, and proportion of positive lymph nodes, lymphovascular invasion and type of treatment were factors affecting survival of the CRC patients. Conclusion: Additive models are suitable alternatives to the Cox proportionality model if there is interest in evaluation of absolute hazard change, or no proportionality assumption is made. Creative Commons Attribution License

[Research advances in mathematical model of coniferous trees cold hardiness].

PubMed

Zhang, Gang; Wang, Ai-Fang

2007-07-01

Plant cold hardiness has complicated attributes. This paper introduced the research advances in establishing the dynamic models of coniferous trees cold hardiness, with the advantages and disadvantages of the models presented and the further studies suggested. In the models established initially, temperature was concerned as the only environmental factor affecting the cold hardiness, and the concept of stationary level of cold hardiness was introduced. Due to the obvious prediction errors of these models, the stationary level of cold hardiness was modeled later by assuming the existence of an additive effect of temperature and photoperiod on the increase of cold hardiness. Furthermore, the responses of the annual development phases for cold hardiness to environment were considered. The model researchers have paid more attention to the additive effect models, and run some experiments to test the additivity principle. However, the research results on Scots pine (Pinus sylvestris) indicated that its organs did not support the presumption of an additive response of cold hardiness by temperature and photoperiod, and the interaction between environmental factors should be taken into account. The mathematical models of cold hardiness need to be developed and improved.

Structured functional additive regression in reproducing kernel Hilbert spaces.

PubMed

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2014-06-01

Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application.

Assessing non-additive effects in GBLUP model.

PubMed

Vieira, I C; Dos Santos, J P R; Pires, L P M; Lima, B M; Gonçalves, F M A; Balestre, M

2017-05-10

Understanding non-additive effects in the expression of quantitative traits is very important in genotype selection, especially in species where the commercial products are clones or hybrids. The use of molecular markers has allowed the study of non-additive genetic effects on a genomic level, in addition to a better understanding of its importance in quantitative traits. Thus, the purpose of this study was to evaluate the behavior of the GBLUP model in different genetic models and relationship matrices and their influence on the estimates of genetic parameters. We used real data of the circumference at breast height in Eucalyptus spp and simulated data from a population of F 2 . Three commonly reported kinship structures in the literature were adopted. The simulation results showed that the inclusion of epistatic kinship improved prediction estimates of genomic breeding values. However, the non-additive effects were not accurately recovered. The Fisher information matrix for real dataset showed high collinearity in estimates of additive, dominant, and epistatic variance, causing no gain in the prediction of the unobserved data and convergence problems. Estimates presented differences of genetic parameters and correlations considering the different kinship structures. Our results show that the inclusion of non-additive effects can improve the predictive ability or even the prediction of additive effects. However, the high distortions observed in the variance estimates when the Hardy-Weinberg equilibrium assumption is violated due to the presence of selection or inbreeding can converge at zero gains in models that consider epistasis in genomic kinship.

Lung Cancer Risk from Occupational and Environmental Radon and Role of Smoking in Two Czech Nested Case-Control Studies

PubMed Central

Tomasek, Ladislav

2013-01-01

The aim of the present study was to evaluate the risk of lung cancer from combined exposure to radon and smoking. Methodologically, it is based on case-control studies nested within two Czech cohort studies of nearly 11,000 miners followed-up for mortality in 1952–2010 and nearly 12,000 inhabitants exposed to high levels of radon in homes, with mortality follow-up in 1960–2010. In addition to recorded radon exposure, these studies use information on smoking collected from the subjects or their relatives. A total of 1,029 and 370 cases with smoking information have been observed in the occupational and environmental (residential) studies, respectively. Three or four control subjects have been individually matched to cases according to sex, year of birth, and age. The combined effect from radon and smoking is analyzed in terms of geometric mixture models of which the additive and multiplicative models are special cases. The resulting models are relatively close to the additive interaction (mixing parameter 0.2 and 0.3 in the occupational and residential studies, respectively). The impact of the resulting model in the residential radon study is illustrated by estimates of lifetime risk in hypothetical populations of smokers and non-smokers. In comparison to the multiplicative risk model, the lifetime risk from the best geometric mixture model is considerably higher, particularly in the non-smoking population. PMID:23470882

[Study on the quantitative evaluation on the degree of TCM basic syndromes often encountered in patients with primary liver cancer].

PubMed

Li, Dong-tao; Ling, Chang-quan; Zhu, De-zeng

2007-07-01

To establish a quantitative model for evaluating the degree of the TCM basic syndromes often encountered in patients with primary liver cancer (PLC). Medical literatures concerning the clinical investigation and TCM syndrome of PLC were collected and analyzed adopting expert-composed symposium method, and the 100 millimeter scaling was applied in combining with scoring on degree of symptoms to establish a quantitative criterion for symptoms and signs degree classification in patients with PLC. Two models, i.e. the additive model and the additive-multiplicative model, were established by using comprehensive analytic hierarchy process (AHP) as the mathematical tool to estimate the weight of the criterion for evaluating basic syndromes in various layers by specialists. Then the two models were verified in clinical practice and the outcomes were compared with that fuzzy evaluated by specialists. Verification on 459 times/case of PLC showed that the coincidence rate between the outcomes derived from specialists with that from the additive model was 84.53 %, and with that from the additive-multificative model was 62.75 %, the difference between the two showed statistical significance (P<0.01). It could be decided that the additive model is the principle model suitable for quantitative evaluation on the degree of TCM basic syndromes in patients with PLC.

Confirming the Multidimensionality of Psychologically Controlling Parenting among Chinese-American Mothers: Love Withdrawal, Guilt Induction, and Shaming.

PubMed

Cheah, Charissa; Yu, Jing; Hart, Craig; Sun, Shuyan; Olsen, Joseph

2015-05-01

Despite the theoretical conceptualization of parental psychological control as a multidimensional construct, the majority of previous studies have examined psychological control as a unidimensional scale. Moreover, the conceptualization of shaming and its associations with love withdrawal and guilt induction are unclear. The current study aimed to fill these gaps by evaluating the latent factor structure underlying 18 items from Olsen et al. (2002) that were conceptually relevant to love withdrawal, guilt induction, and shaming practices in a sample of 169 mothers of Chinese-American preschoolers. A multidimensional three-factor model and bi-factor model were specified based on our formulated operational definitions for the three dimensions of psychological control. Both models were found to be superior to the unidimensional model. In addition, results from the bi-factor model and an additional second-order factor model indicated that psychological control is essentially empirically isomorphic with guilt induction. Although love withdrawal and shaming factors were also fairly strong indicators of psychological control, each exhibited important additional unique variability and mutual distinctiveness. Implications for the conceptualization of love withdrawal, guilt induction, and shaming as well as directions for future studies are discussed.

Confirming the Multidimensionality of Psychologically Controlling Parenting among Chinese-American Mothers: Love Withdrawal, Guilt Induction, and Shaming

PubMed Central

Cheah, Charissa; Yu, Jing; Hart, Craig; Sun, Shuyan; Olsen, Joseph

2014-01-01

Despite the theoretical conceptualization of parental psychological control as a multidimensional construct, the majority of previous studies have examined psychological control as a unidimensional scale. Moreover, the conceptualization of shaming and its associations with love withdrawal and guilt induction are unclear. The current study aimed to fill these gaps by evaluating the latent factor structure underlying 18 items from Olsen et al. (2002) that were conceptually relevant to love withdrawal, guilt induction, and shaming practices in a sample of 169 mothers of Chinese-American preschoolers. A multidimensional three-factor model and bi-factor model were specified based on our formulated operational definitions for the three dimensions of psychological control. Both models were found to be superior to the unidimensional model. In addition, results from the bi-factor model and an additional second-order factor model indicated that psychological control is essentially empirically isomorphic with guilt induction. Although love withdrawal and shaming factors were also fairly strong indicators of psychological control, each exhibited important additional unique variability and mutual distinctiveness. Implications for the conceptualization of love withdrawal, guilt induction, and shaming as well as directions for future studies are discussed. PMID:26052168

Effects of some polymeric additives on the cocrystallization of caffeine

NASA Astrophysics Data System (ADS)

Chung, Jihae; Kim, Il Won

2011-11-01

Effects of polymeric additives on the model cocrystallization were examined. The model cocrystal was made from caffeine and oxalic acid, and poly(ethylene glycol) (PEG), poly( L-lactide) (PLLA), poly(ɛ-caprolactone) (PCL), and poly(acrylic acid) (PAA) were the additives. The cocrystals were formed as millimeter-sized crystals without additives, and they became microcrystals with PLLA and PCL, and nanocrystals with PAA. XRD and IR revealed that the cocrystal structure was unchanged despite the strong effects of the additives on the crystal morphology, although some decrease in crystallinity was observed with PAA as confirmed by DSC. The DSC study also showed that the cocrystal melted and recrystallized to form α-caffeine upon heating. The present study verified that the polymeric additives can be utilized to modulate the size and morphology of the cocrystals without interfering the intermolecular interactions essential to the integrity of the cocrystal structures.

Influence of Polarization on Carbohydrate Hydration: A Comparative Study Using Additive and Polarizable Force Fields.

PubMed

Pandey, Poonam; Mallajosyula, Sairam S

2016-07-14

Carbohydrates are known to closely modulate their surrounding solvent structures and influence solvation dynamics. Spectroscopic investigations studying far-IR regions (below 1000 cm(-1)) have observed spectral shifts in the libration band (around 600 cm(-1)) of water in the presence of monosaccharides and polysaccharides. In this paper, we use molecular dynamics simulations to gain atomistic insight into carbohydrate-water interactions and to specifically highlight the differences between additive (nonpolarizable) and polarizable simulations. A total of six monosaccharide systems, α and β anomers of glucose, galactose, and mannose, were studied using additive and polarizable Chemistry at HARvard Macromolecular Mechanics (CHARMM) carbohydrate force fields. Solvents were modeled using three additive water models TIP3P, TIP4P, and TIP5P in additive simulations and polarizable water model SWM4 in polarizable simulations. The presence of carbohydrate has a significant effect on the microscopic water structure, with the effects being pronounced for proximal water molecules. Notably, disruption of the tetrahedral arrangement of proximal water molecules was observed due to the formation of strong carbohydrate-water hydrogen bonds in both additive and polarizable simulations. However, the inclusion of polarization resulted in significant water-bridge occupancies, improved ordered water structures (tetrahedral order parameter), and longer carbohydrate-water H-bond correlations as compared to those for additive simulations. Additionally, polarizable simulations also allowed the calculation of power spectra from the dipole-dipole autocorrelation function, which corresponds to the IR spectra. From the power spectra, we could identify spectral signatures differentiating the proximal and bulk water structures, which could not be captured from additive simulations.

Formation and reduction of carcinogenic furan in various model systems containing food additives.

PubMed

Kim, Jin-Sil; Her, Jae-Young; Lee, Kwang-Geun

2015-12-15

The aim of this study was to analyse and reduce furan in various model systems. Furan model systems consisting of monosaccharides (0.5M glucose and ribose), amino acids (0.5M alanine and serine) and/or 1.0M ascorbic acid were heated at 121°C for 25 min. The effects of food additives (each 0.1M) such as metal ions (iron sulphate, magnesium sulphate, zinc sulphate and calcium sulphate), antioxidants (BHT and BHA), and sodium sulphite on the formation of furan were measured. The level of furan formed in the model systems was 6.8-527.3 ng/ml. The level of furan in the model systems of glucose/serine and glucose/alanine increased 7-674% when food additives were added. In contrast, the level of furan decreased by 18-51% in the Maillard reaction model systems that included ribose and alanine/serine with food additives except zinc sulphate. Copyright © 2014 Elsevier Ltd. All rights reserved.

Updated determination of stress parameters for nine well-recorded earthquakes in eastern North America

USGS Publications Warehouse

Boore, David M.

2012-01-01

Stress parameters (Δσ) are determined for nine relatively well-recorded earthquakes in eastern North America for ten attenuation models. This is an update of a previous study by Boore et al. (2010). New to this paper are observations from the 2010 Val des Bois earthquake, additional observations for the 1988 Saguenay and 2005 Riviere du Loup earthquakes, and consideration of six attenuation models in addition to the four used in the previous study. As in that study, it is clear that Δσ depends strongly on the rate of geometrical spreading (as well as other model parameters). The observations necessary to determine conclusively which attenuation model best fits the data are still lacking. At this time, a simple 1/R model seems to give as good an overall fit to the data as more complex models.

Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PubMed

Baquero, Oswaldo Santos; Santana, Lidia Maria Reis; Chiaravalloti-Neto, Francisco

2018-01-01

Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in turn, timely and efficient interventions to reduce the burden of the disease. We conducted a comparative study of dengue predictions in São Paulo city to test the performance of trained seasonal autoregressive integrated moving average models, generalized additive models and artificial neural networks. We also used a naïve model as a benchmark. A generalized additive model with lags of the number of cases and meteorological variables had the best performance, predicted epidemics of unprecedented magnitude and its performance was 3.16 times higher than the benchmark and 1.47 higher that the next best performing model. The predictive models captured the seasonal patterns but differed in their capacity to anticipate large epidemics and all outperformed the benchmark. In addition to be able to predict epidemics of unprecedented magnitude, the best model had computational advantages, since its training and tuning was straightforward and required seconds or at most few minutes. These are desired characteristics to provide timely results for decision makers. However, it should be noted that predictions are made just one month ahead and this is a limitation that future studies could try to reduce.

A MIXTURE OF SEVEN ANTIANDROGENIC COMPOUNDS ELICITS ADDITIVE EFFECTS ON THE MALE RAT REPRODUCTIVE TRACT THAT CORRESPOND TO MODELED PREDICTIONS

EPA Science Inventory

The main objectives of this study were to: (1) determine whether dissimilar antiandrogenic compounds display additive effects when present in combination and (2) to assess the ability of modelling approaches to accurately predict these mixture effects based on data from single ch...

Rain water transport and storage in a model sandy soil with hydrogel particle additives.

PubMed

Wei, Y; Durian, D J

2014-10-01

We study rain water infiltration and drainage in a dry model sandy soil with superabsorbent hydrogel particle additives by measuring the mass of retained water for non-ponding rainfall using a self-built 3D laboratory set-up. In the pure model sandy soil, the retained water curve measurements indicate that instead of a stable horizontal wetting front that grows downward uniformly, a narrow fingered flow forms under the top layer of water-saturated soil. This rain water channelization phenomenon not only further reduces the available rain water in the plant root zone, but also affects the efficiency of soil additives, such as superabsorbent hydrogel particles. Our studies show that the shape of the retained water curve for a soil packing with hydrogel particle additives strongly depends on the location and the concentration of the hydrogel particles in the model sandy soil. By carefully choosing the particle size and distribution methods, we may use the swollen hydrogel particles to modify the soil pore structure, to clog or extend the water channels in sandy soils, or to build water reservoirs in the plant root zone.

Effectiveness of the Touch Math Technique in Teaching Basic Addition to Children with Autism

ERIC Educational Resources Information Center

Yikmis, Ahmet

2016-01-01

This study aims to reveal whether the touch math technique is effective in teaching basic addition to children with autism. The dependent variable of this study is the children's skills to solve addition problems correctly, whereas teaching with the touch math technique is the independent variable. Among the single-subject research models, a…

Structured functional additive regression in reproducing kernel Hilbert spaces

PubMed Central

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2013-01-01

Summary Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application. PMID:25013362

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Nitrogen deposition and soil carbon sequestration: enzymes, experiments, and model estimates (Invited)

NASA Astrophysics Data System (ADS)

Goodale, C. L.; Weiss, M.; Tonitto, C.; Stone, M.

2010-12-01

Atmospheric nitrogen has long been expected to increase forest carbon sequestration, by means of enhanced productivity and litter production. More recently, N deposition has received attention for its potential for inducing soil C sequestration by suppressing microbial decomposition. Here, we present a range of measurements and model projections of the effects of N additions on soil C dynamics in forest soils of the northeastern U.S. A review of field-scale measurements of soil C stocks suggests modest enhancements of soil C storage in long-term N addition studies. Measurements of forest floor material from six long-term N addition studies showed that N additions suppressed microbial biomass and oxidative enzyme activity across sites. Additional analyses on soils from two of these sites are exploring the interactive effects of temperature and N addition on the activity of a range of extracellular enzymes used for decomposition of a range of organic matter. Incubations of forest floor material from four of these sites showed inhibition of heterotrophic respiration by an average of 28% during the first week of incubation, although this inhibition disappeared after 2 to 11 months. Nitrogen additions had no significant effect on DOC loss or on the partitioning of soil C into light or heavy (mineral-associated) organic matter. Last, we have adapted a new model of soil organic matter decomposition for the PnET-CN model to assess the long-term impact of suppressed decomposition on C sequestration in various soil C pools.

A Single-Boundary Accumulator Model of Response Times in an Addition Verification Task

PubMed Central

Faulkenberry, Thomas J.

2017-01-01

Current theories of mathematical cognition offer competing accounts of the interplay between encoding and calculation in mental arithmetic. Additive models propose that manipulations of problem format do not interact with the cognitive processes used in calculation. Alternatively, interactive models suppose that format manipulations have a direct effect on calculation processes. In the present study, we tested these competing models by fitting participants' RT distributions in an arithmetic verification task with a single-boundary accumulator model (the shifted Wald distribution). We found that in addition to providing a more complete description of RT distributions, the accumulator model afforded a potentially more sensitive test of format effects. Specifically, we found that format affected drift rate, which implies that problem format has a direct impact on calculation processes. These data give further support for an interactive model of mental arithmetic. PMID:28769853

Force Field for Peptides and Proteins based on the Classical Drude Oscillator

PubMed Central

Lopes, Pedro E.M.; Huang, Jing; Shim, Jihyun; Luo, Yun; Li, Hui; Roux, Benoît; MacKerell, Alexander D.

2013-01-01

Presented is a polarizable force field based on a classical Drude oscillator framework, currently implemented in the programs CHARMM and NAMD, for modeling and molecular dynamics (MD) simulation studies of peptides and proteins. Building upon parameters for model compounds representative of the functional groups in proteins, the development of the force field focused on the optimization of the parameters for the polypeptide backbone and the connectivity between the backbone and side chains. Optimization of the backbone electrostatic parameters targeted quantum mechanical conformational energies, interactions with water, molecular dipole moments and polarizabilities and experimental condensed phase data for short polypeptides such as (Ala)5. Additional optimization of the backbone φ, ψ conformational preferences included adjustments of the tabulated two-dimensional spline function through the CMAP term. Validation of the model included simulations of a collection of peptides and proteins. This 1st generation polarizable model is shown to maintain the folded state of the studied systems on the 100 ns timescale in explicit solvent MD simulations. The Drude model typically yields larger RMS differences as compared to the additive CHARMM36 force field (C36) and shows additional flexibility as compared to the additive model. Comparison with NMR chemical shift data shows a small degradation of the polarizable model with respect to the additive, though the level of agreement may be considered satisfactory, while for residues shown to have significantly underestimated S2 order parameters in the additive model, improvements are calculated with the polarizable model. Analysis of dipole moments associated with the peptide backbone and tryptophan side chains show the Drude model to have significantly larger values than those present in C36, with the dipole moments of the peptide backbone enhanced to a greater extent in sheets versus helices and the dipoles of individual moieties observed to undergo significant variations during the MD simulations. Although there are still some limitations, the presented model, termed Drude-2013, is anticipated to yield a molecular picture of peptide and protein structure and function that will be of increased physical validity and internal consistency in a computationally accessible fashion. PMID:24459460

Transient Properties of Probability Distribution for a Markov Process with Size-dependent Additive Noise

NASA Astrophysics Data System (ADS)

Yamada, Yuhei; Yamazaki, Yoshihiro

2018-04-01

This study considered a stochastic model for cluster growth in a Markov process with a cluster size dependent additive noise. According to this model, the probability distribution of the cluster size transiently becomes an exponential or a log-normal distribution depending on the initial condition of the growth. In this letter, a master equation is obtained for this model, and derivation of the distributions is discussed.

Genomic Model with Correlation Between Additive and Dominance Effects.

PubMed

Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

2018-05-09

Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant deviations performed similarly for prediction. Copyright © 2018, Genetics.

Covariate adjustment of event histories estimated from Markov chains: the additive approach.

PubMed

Aalen, O O; Borgan, O; Fekjaer, H

2001-12-01

Markov chain models are frequently used for studying event histories that include transitions between several states. An empirical transition matrix for nonhomogeneous Markov chains has previously been developed, including a detailed statistical theory based on counting processes and martingales. In this article, we show how to estimate transition probabilities dependent on covariates. This technique may, e.g., be used for making estimates of individual prognosis in epidemiological or clinical studies. The covariates are included through nonparametric additive models on the transition intensities of the Markov chain. The additive model allows for estimation of covariate-dependent transition intensities, and again a detailed theory exists based on counting processes. The martingale setting now allows for a very natural combination of the empirical transition matrix and the additive model, resulting in estimates that can be expressed as stochastic integrals, and hence their properties are easily evaluated. Two medical examples will be given. In the first example, we study how the lung cancer mortality of uranium miners depends on smoking and radon exposure. In the second example, we study how the probability of being in response depends on patient group and prophylactic treatment for leukemia patients who have had a bone marrow transplantation. A program in R and S-PLUS that can carry out the analyses described here has been developed and is freely available on the Internet.

Ridge, Lasso and Bayesian additive-dominance genomic models.

PubMed

Azevedo, Camila Ferreira; de Resende, Marcos Deon Vilela; E Silva, Fabyano Fonseca; Viana, José Marcelo Soriano; Valente, Magno Sávio Ferreira; Resende, Márcio Fernando Ribeiro; Muñoz, Patricio

2015-08-25

A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes). G-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close. Amongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (-2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.

Doubly Robust Additive Hazards Models to Estimate Effects of a Continuous Exposure on Survival.

PubMed

Wang, Yan; Lee, Mihye; Liu, Pengfei; Shi, Liuhua; Yu, Zhi; Abu Awad, Yara; Zanobetti, Antonella; Schwartz, Joel D

2017-11-01

The effect of an exposure on survival can be biased when the regression model is misspecified. Hazard difference is easier to use in risk assessment than hazard ratio and has a clearer interpretation in the assessment of effect modifications. We proposed two doubly robust additive hazards models to estimate the causal hazard difference of a continuous exposure on survival. The first model is an inverse probability-weighted additive hazards regression. The second model is an extension of the doubly robust estimator for binary exposures by categorizing the continuous exposure. We compared these with the marginal structural model and outcome regression with correct and incorrect model specifications using simulations. We applied doubly robust additive hazard models to the estimation of hazard difference of long-term exposure to PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 microns) on survival using a large cohort of 13 million older adults residing in seven states of the Southeastern United States. We showed that the proposed approaches are doubly robust. We found that each 1 μg m increase in annual PM2.5 exposure was associated with a causal hazard difference in mortality of 8.0 × 10 (95% confidence interval 7.4 × 10, 8.7 × 10), which was modified by age, medical history, socioeconomic status, and urbanicity. The overall hazard difference translates to approximately 5.5 (5.1, 6.0) thousand deaths per year in the study population. The proposed approaches improve the robustness of the additive hazards model and produce a novel additive causal estimate of PM2.5 on survival and several additive effect modifications, including social inequality.

Sidewalk undermining studies : phase III, field and model studies.

DOT National Transportation Integrated Search

1979-01-01

The results of the early studies of the undermining problems are summarized in the initial portion of this report. Additionally, the design and use of a model sidewalk for testing procedures for preventing undermining are described. Based upon tests ...

Interaction of actin filaments with the plasma membrane in Amoeba proteus: studies using a cell model and isolated plasma membrane.

PubMed

Kawakatsu, T; Kikuchi, A; Shimmen, T; Sonobe, S

2000-08-01

We prepared a cell model of Amoeba proteus by mechanical bursting to study the interaction between actin filaments (AFs) and plasma membrane (PM). The cell model prepared in the absence of Ca2+ showed remarkable contraction upon addition of ATP. When the model was prepared in the presence of Ca2+, the cytoplasmic granules formed an aggregate in the central region, having moved away from PM. Although this model showed contraction upon addition of ATP in the presence of Ca2+, less contraction was noted. Staining with rhodamine-phalloidin revealed association of AFs with PM in the former model, and a lesser amount of association in the latter model. The interaction between AFs and PM was also studied using the isolated PM. AFs were associated with PM isolated in the absence of Ca2+, but were not when Ca2+ was present. These results suggest that the interaction between AFs and PM is regulated by Ca2+.

An Analysis of Kindergarten and First Grade Children's Addition and Subtraction Problem Solving Modeling and Accuracy.

ERIC Educational Resources Information Center

Shores, Jay H.; Underhill, Robert G.

A study was undertaken of the effects of formal education and conservation of numerousness on addition and subtraction problem types. Thirty-six kindergarten and 36 first-grade subjects randomly selected from one area of a school district were administered measures of conservation, problem-solving success, and modeling ability. Following factor…

Enhanced risk prediction model for emergency department use and hospitalizations in patients in a primary care medical home.

PubMed

Takahashi, Paul Y; Heien, Herbert C; Sangaralingham, Lindsey R; Shah, Nilay D; Naessens, James M

2016-07-01

With the advent of healthcare payment reform, identifying high-risk populations has become more important to providers. Existing risk-prediction models often focus on chronic conditions. This study sought to better understand other factors to improve identification of the highest risk population. A retrospective cohort study of a paneled primary care population utilizing 2010 data to calibrate a risk prediction model of hospital and emergency department (ED) use in 2011. Data were randomly split into development and validation data sets. We compared the enhanced model containing the additional risk predictors with the Minnesota medical tiering model. The study was conducted in the primary care practice of an integrated delivery system at an academic medical center in Rochester, Minnesota. The study focus was primary care medical home patients in 2010 and 2011 (n = 84,752), with the primary outcome of subsequent hospitalization or ED visit. A total of 42,384 individuals derived the enhanced risk-prediction model and 42,368 individuals validated the model. Predictors included Adjusted Clinical Groups-based Minnesota medical tiering, patient demographics, insurance status, and prior year healthcare utilization. Additional variables included specific mental and medical conditions, use of high-risk medications, and body mass index. The area under the curve in the enhanced model was 0.705 (95% CI, 0.698-0.712) compared with 0.662 (95% CI, 0.656-0.669) in the Minnesota medical tiering-only model. New high-risk patients in the enhanced model were more likely to have lack of health insurance, presence of Medicaid, diagnosed depression, and prior ED utilization. An enhanced model including additional healthcare-related factors improved the prediction of risk of hospitalization or ED visit.

Elucidating the fate of a mixed toluene, DHM, methanol, and i-propanol plume during in situ bioremediation

NASA Astrophysics Data System (ADS)

Verardo, E.; Atteia, O.; Prommer, H.

2017-06-01

Organic pollutants such as solvents or petroleum products are widespread contaminants in soil and groundwater systems. In-situ bioremediation is a commonly used remediation technology to clean up the subsurface to eliminate the risks of toxic substances to reach potential receptors in surface waters or drinking water wells. This study discusses the development of a subsurface model to analyse the performance of an actively operating field-scale enhanced bioremediation scheme. The study site was affected by a mixed toluene, dihydromyrcenol (DHM), methanol, and i-propanol plume. A high-resolution, time-series of data was used to constrain the model development and calibration. The analysis shows that the observed failure of the treatment system is linked to an inefficient oxygen injection pattern. Moreover, the model simulations also suggest that additional contaminant spillages have occurred in 2012. Those additional spillages and their associated additional oxygen demand resulted in a significant increase in contaminant fluxes that remained untreated. The study emphasises the important role that reactive transport modelling can play in data analyses and for enhancing remediation efficiency.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Teaching physical activities to students with significant disabilities using video modeling.

PubMed

Cannella-Malone, Helen I; Mizrachi, Sharona V; Sabielny, Linsey M; Jimenez, Eliseo D

2013-06-01

The objective of this study was to examine the effectiveness of video modeling on teaching physical activities to three adolescents with significant disabilities. The study implemented a multiple baseline across six physical activities (three per student): jumping rope, scooter board with cones, ladder drill (i.e., feet going in and out), ladder design (i.e., multiple steps), shuttle run, and disc ride. Additional prompt procedures (i.e., verbal, gestural, visual cues, and modeling) were implemented within the study. After the students mastered the physical activities, we tested to see if they would link the skills together (i.e., complete an obstacle course). All three students made progress learning the physical activities, but only one learned them with video modeling alone (i.e., without error correction). Video modeling can be an effective tool for teaching students with significant disabilities various physical activities, though additional prompting procedures may be needed.

Silkworm: A Promising Model Organism in Life Science.

PubMed

Meng, Xu; Zhu, Feifei; Chen, Keping

2017-09-01

As an important economic insect, silkworm Bombyx mori (L.) (Lepidoptera: Bombycidae) has numerous advantages in life science, such as low breeding cost, large progeny size, short generation time, and clear genetic background. Additionally, there are rich genetic resources associated with silkworms. The completion of the silkworm genome has further accelerated it to be a modern model organism in life science. Genomic studies showed that some silkworm genes are highly homologous to certain genes related to human hereditary disease and, therefore, are a candidate model for studying human disease. In this article, we provided a review of silkworm as an important model in various research areas, including human disease, screening of antimicrobial agents, environmental safety monitoring, and antitumor studies. In addition, the application potentiality of silkworm model in life sciences was discussed. © The Author 2017. Published by Oxford University Press on behalf of Entomological Society of America.

Measurements of Student and Teacher Perceptions of Co-Teaching Models

ERIC Educational Resources Information Center

Keeley, Randa G.

2015-01-01

Co-teaching is an accepted teaching model for inclusive classrooms. This study measured the perceptions of both students and teachers regarding the five most commonly used co-teaching models (i.e., One Teach/One Assist, Station Teaching, Alternative Teaching, Parallel Teaching, and Team Teaching). Additionally, this study compared student…

Marginal regression approach for additive hazards models with clustered current status data.

PubMed

Su, Pei-Fang; Chi, Yunchan

2014-01-15

Current status data arise naturally from tumorigenicity experiments, epidemiology studies, biomedicine, econometrics and demographic and sociology studies. Moreover, clustered current status data may occur with animals from the same litter in tumorigenicity experiments or with subjects from the same family in epidemiology studies. Because the only information extracted from current status data is whether the survival times are before or after the monitoring or censoring times, the nonparametric maximum likelihood estimator of survival function converges at a rate of n(1/3) to a complicated limiting distribution. Hence, semiparametric regression models such as the additive hazards model have been extended for independent current status data to derive the test statistics, whose distributions converge at a rate of n(1/2) , for testing the regression parameters. However, a straightforward application of these statistical methods to clustered current status data is not appropriate because intracluster correlation needs to be taken into account. Therefore, this paper proposes two estimating functions for estimating the parameters in the additive hazards model for clustered current status data. The comparative results from simulation studies are presented, and the application of the proposed estimating functions to one real data set is illustrated. Copyright © 2013 John Wiley & Sons, Ltd.

Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits.

PubMed

Aliloo, Hassan; Pryce, Jennie E; González-Recio, Oscar; Cocks, Benjamin G; Hayes, Ben J

2016-02-01

Dominance effects may contribute to genetic variation of complex traits in dairy cattle, especially for traits closely related to fitness such as fertility. However, traditional genetic evaluations generally ignore dominance effects and consider additive genetic effects only. Availability of dense single nucleotide polymorphisms (SNPs) panels provides the opportunity to investigate the role of dominance in quantitative variation of complex traits at both the SNP and animal levels. Including dominance effects in the genomic evaluation of animals could also help to increase the accuracy of prediction of future phenotypes. In this study, we estimated additive and dominance variance components for fertility and milk production traits of genotyped Holstein and Jersey cows in Australia. The predictive abilities of a model that accounts for additive effects only (additive), and a model that accounts for both additive and dominance effects (additive + dominance) were compared in a fivefold cross-validation. Estimates of the proportion of dominance variation relative to phenotypic variation that is captured by SNPs, for production traits, were up to 3.8 and 7.1 % in Holstein and Jersey cows, respectively, whereas, for fertility, they were equal to 1.2 % in Holstein and very close to zero in Jersey cows. We found that including dominance in the model was not consistently advantageous. Based on maximum likelihood ratio tests, the additive + dominance model fitted the data better than the additive model, for milk, fat and protein yields in both breeds. However, regarding the prediction of phenotypes assessed with fivefold cross-validation, including dominance effects in the model improved accuracy only for fat yield in Holstein cows. Regression coefficients of phenotypes on genetic values and mean squared errors of predictions showed that the predictive ability of the additive + dominance model was superior to that of the additive model for some of the traits. In both breeds, dominance effects were significant (P < 0.01) for all milk production traits but not for fertility. Accuracy of prediction of phenotypes was slightly increased by including dominance effects in the genomic evaluation model. Thus, it can help to better identify highly performing individuals and be useful for culling decisions.

From an animal model to human patients: An example of a translational study on obsessive compulsive disorder (OCD).

PubMed

Eilam, David

2017-05-01

The application of similar analyses enables a direct projection from translational research in animals to human studies. Following is an example of how the methodology of a specific animal model of obsessive-compulsive disorder (OCD) was applied to study human patients. Specifically, the quinpirole rat model for OCD was based on analyzing the trajectories of travel among different locales, and scoring the set of acts performed at each locale. Applying this analytic approach in human patients unveiled various aspects of OCD, such as the repetition and addition of acts, incompleteness, and the link between behavior and specific locations. It is also illustrated how the same analytical approach could be applicable to studying other mental disorders. Finally, it is suggested that the development of OCD could be explained by the four-phase sequence of Repetition, Addition, Condensation, and Elimination, as outlined in the study of ontogeny and phylogeny and applied to normal development of behavior. In OCD, this sequence is curtailed, resulting in the abundant repetition and addition of acts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Risk of Type 2 Diabetes Mellitus with Genetic Risk Models on the Basis of Established Genome-wide Association Markers: A Systematic Review

PubMed Central

Bao, Wei; Hu, Frank B.; Rong, Shuang; Rong, Ying; Bowers, Katherine; Schisterman, Enrique F.; Liu, Liegang; Zhang, Cuilin

2013-01-01

This study aimed to evaluate the predictive performance of genetic risk models based on risk loci identified and/or confirmed in genome-wide association studies for type 2 diabetes mellitus. A systematic literature search was conducted in the PubMed/MEDLINE and EMBASE databases through April 13, 2012, and published data relevant to the prediction of type 2 diabetes based on genome-wide association marker–based risk models (GRMs) were included. Of the 1,234 potentially relevant articles, 21 articles representing 23 studies were eligible for inclusion. The median area under the receiver operating characteristic curve (AUC) among eligible studies was 0.60 (range, 0.55–0.68), which did not differ appreciably by study design, sample size, participants’ race/ethnicity, or the number of genetic markers included in the GRMs. In addition, the AUCs for type 2 diabetes did not improve appreciably with the addition of genetic markers into conventional risk factor–based models (median AUC, 0.79 (range, 0.63–0.91) vs. median AUC, 0.78 (range, 0.63–0.90), respectively). A limited number of included studies used reclassification measures and yielded inconsistent results. In conclusion, GRMs showed a low predictive performance for risk of type 2 diabetes, irrespective of study design, participants’ race/ethnicity, and the number of genetic markers included. Moreover, the addition of genome-wide association markers into conventional risk models produced little improvement in predictive performance. PMID:24008910

Magnetic x-ray scattering studies of holmium using synchro- tron radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gibbs, D.; Moncton, D.E.; D'Amico, K.L.

1985-07-08

We present the results of magnetic x-ray scattering experiments on the rare-earth metal holmium using synchrotron radiation. Direct high-resolution measurements of the nominally incommensurate magnetic satellite reflections reveal new lock-in behavior which we explain within a simple spin-discommensuration model. As a result of magnetoelastic coupling, the spin-discommensuration array produces additional x-ray diffraction satellites. Their observation further substantiates the model and demonstrates additional advantages of synchrotron radiation for magnetic-structure studies.

Quantification of Treatment Effect Modification on Both an Additive and Multiplicative Scale

PubMed Central

Girerd, Nicolas; Rabilloud, Muriel; Pibarot, Philippe; Mathieu, Patrick; Roy, Pascal

2016-01-01

Background In both observational and randomized studies, associations with overall survival are by and large assessed on a multiplicative scale using the Cox model. However, clinicians and clinical researchers have an ardent interest in assessing absolute benefit associated with treatments. In older patients, some studies have reported lower relative treatment effect, which might translate into similar or even greater absolute treatment effect given their high baseline hazard for clinical events. Methods The effect of treatment and the effect modification of treatment were respectively assessed using a multiplicative and an additive hazard model in an analysis adjusted for propensity score in the context of coronary surgery. Results The multiplicative model yielded a lower relative hazard reduction with bilateral internal thoracic artery grafting in older patients (Hazard ratio for interaction/year = 1.03, 95%CI: 1.00 to 1.06, p = 0.05) whereas the additive model reported a similar absolute hazard reduction with increasing age (Delta for interaction/year = 0.10, 95%CI: -0.27 to 0.46, p = 0.61). The number needed to treat derived from the propensity score-adjusted multiplicative model was remarkably similar at the end of the follow-up in patients aged < = 60 and in patients >70. Conclusions The present example demonstrates that a lower treatment effect in older patients on a relative scale can conversely translate into a similar treatment effect on an additive scale due to large baseline hazard differences. Importantly, absolute risk reduction, either crude or adjusted, can be calculated from multiplicative survival models. We advocate for a wider use of the absolute scale, especially using additive hazard models, to assess treatment effect and treatment effect modification. PMID:27045168

Adding thin-ideal internalization and impulsiveness to the cognitive-behavioral model of bulimic symptoms.

PubMed

Schnitzler, Caroline E; von Ranson, Kristin M; Wallace, Laurel M

2012-08-01

This study evaluated the cognitive-behavioral (CB) model of bulimia nervosa and an extension that included two additional maintaining factors - thin-ideal internalization and impulsiveness - in 327 undergraduate women. Participants completed measures of demographics, self-esteem, concern about shape and weight, dieting, bulimic symptoms, thin-ideal internalization, and impulsiveness. Both the original CB model and the extended model provided good fits to the data. Although structural equation modeling analyses suggested that the original CB model was most parsimonious, hierarchical regression analyses indicated that the additional variables accounted for significantly more variance. Additional analyses showed that the model fit could be improved by adding a path from concern about shape and weight, and deleting the path from dieting, to bulimic symptoms. Expanding upon the factors considered in the model may better capture the scope of variables maintaining bulimic symptoms in young women with a range of severity of bulimic symptoms. Copyright © 2012 Elsevier Ltd. All rights reserved.

The technology acceptance model: its past and its future in health care.

PubMed

Holden, Richard J; Karsh, Ben-Tzion

2010-02-01

Increasing interest in end users' reactions to health information technology (IT) has elevated the importance of theories that predict and explain health IT acceptance and use. This paper reviews the application of one such theory, the Technology Acceptance Model (TAM), to health care. We reviewed 16 data sets analyzed in over 20 studies of clinicians using health IT for patient care. Studies differed greatly in samples and settings, health ITs studied, research models, relationships tested, and construct operationalization. Certain TAM relationships were consistently found to be significant, whereas others were inconsistent. Several key relationships were infrequently assessed. Findings show that TAM predicts a substantial portion of the use or acceptance of health IT, but that the theory may benefit from several additions and modifications. Aside from improved study quality, standardization, and theoretically motivated additions to the model, an important future direction for TAM is to adapt the model specifically to the health care context, using beliefs elicitation methods.

THE TECHNOLOGY ACCEPTANCE MODEL: ITS PAST AND ITS FUTURE IN HEALTH CARE

PubMed Central

HOLDEN, RICHARD J.; KARSH, BEN-TZION

2009-01-01

Increasing interest in end users’ reactions to health information technology (IT) has elevated the importance of theories that predict and explain health IT acceptance and use. This paper reviews the application of one such theory, the Technology Acceptance Model (TAM), to health care. We reviewed 16 data sets analyzed in over 20 studies of clinicians using health IT for patient care. Studies differed greatly in samples and settings, health ITs studied, research models, relationships tested, and construct operationalization. Certain TAM relationships were consistently found to be significant, whereas others were inconsistent. Several key relationships were infrequently assessed. Findings show that TAM predicts a substantial portion of the use or acceptance of health IT, but that the theory may benefit from several additions and modifications. Aside from improved study quality, standardization, and theoretically motivated additions to the model, an important future direction for TAM is to adapt the model specifically to the health care context, using beliefs elicitation methods. PMID:19615467

A family of triaxial modified Hubble mass models: Effects of the additional radial functions

NASA Astrophysics Data System (ADS)

Das, Mousumi; Thakur, Parijat; Ann, H. B.

2005-03-01

The projected properties of triaxial generalization of the modified Hubble mass models are studied. These models are constructed by adding the additional radial functions, each multiplied by a low-order spherical harmonic, to the models of [Chakraborty, D.K., Thakur, P., 2000. MNRAS 318, 1273]. The projected surface density of mass models can be calculated analytically which allows us to derive the analytic expressions of axial ratio and position angle of major axis of constant density elliptical contours at asymptotic radii. The models are more general than those studied earlier in the sense that the inclusions of additional terms in density distribution, allow one to produce varieties of the radial profile of axial ratio and position angle, in particular, their small scale variations at inner radii. Strong correlations are found to exist between the observed axial ratio evaluated at 0.25Re and at 4Re which occupy well-separated regions in the parameter space for different choices of the intrinsic axial ratios. These correlations can be exploited to predict the intrinsic shape of the mass model, independent of the viewing angles. Using Bayesian statistics, the result of a test case launched for an estimation of the shape of a model galaxy is found to be satisfactory.

Boundary layer integral matrix procedure: Verification of models

NASA Technical Reports Server (NTRS)

Bonnett, W. S.; Evans, R. M.

1977-01-01

The three turbulent models currently available in the JANNAF version of the Aerotherm Boundary Layer Integral Matrix Procedure (BLIMP-J) code were studied. The BLIMP-J program is the standard prediction method for boundary layer effects in liquid rocket engine thrust chambers. Experimental data from flow fields with large edge-to-wall temperature ratios are compared to the predictions of the three turbulence models contained in BLIMP-J. In addition, test conditions necessary to generate additional data on a flat plate or in a nozzle are given. It is concluded that the Cebeci-Smith turbulence model be the recommended model for the prediction of boundary layer effects in liquid rocket engines. In addition, the effects of homogeneous chemical reaction kinetics were examined for a hydrogen/oxygen system. Results show that for most flows, kinetics are probably only significant for stoichiometric mixture ratios.

The Job Demands-Resources Model: An Analysis of Additive and Joint Effects of Demands and Resources

ERIC Educational Resources Information Center

Hu, Qiao; Schaufeli, Wilmar B.; Taris, Toon W.

2011-01-01

The present study investigated the additive, synergistic, and moderating effects of job demands and job resources on well-being (burnout and work engagement) and organizational outcomes, as specified by the Job Demands-Resources (JD-R) model. A survey was conducted among two Chinese samples: 625 blue collar workers and 761 health professionals. A…

Optimizing simulated fertilizer additions using a genetic algorithm with a nutrient uptake model

Treesearch

Wendell P. Cropper; N.B. Comerford

2005-01-01

Intensive management of pine plantations in the southeastern coastal plain typically involves weed and pest control, and the addition of fertilizer to meet the high nutrient demand of rapidly growing pines. In this study we coupled a mechanistic nutrient uptake model (SSAND, soil supply and nutrient demand) with a genetic algorithm (GA) in order to estimate the minimum...

The prediction of food additives in the fruit juice based on electronic nose with chemometrics.

PubMed

Qiu, Shanshan; Wang, Jun

2017-09-01

Food additives are added to products to enhance their taste, and preserve flavor or appearance. While their use should be restricted to achieve a technological benefit, the contents of food additives should be also strictly controlled. In this study, E-nose was applied as an alternative to traditional monitoring technologies for determining two food additives, namely benzoic acid and chitosan. For quantitative monitoring, support vector machine (SVM), random forest (RF), extreme learning machine (ELM) and partial least squares regression (PLSR) were applied to establish regression models between E-nose signals and the amount of food additives in fruit juices. The monitoring models based on ELM and RF reached higher correlation coefficients (R 2 s) and lower root mean square errors (RMSEs) than models based on PLSR and SVM. This work indicates that E-nose combined with RF or ELM can be a cost-effective, easy-to-build and rapid detection system for food additive monitoring. Copyright © 2017 Elsevier Ltd. All rights reserved.

Animal models for dengue vaccine development and testing

PubMed Central

2017-01-01

Dengue fever is a tropical endemic disease; however, because of climate change, it may become a problem in South Korea in the near future. Research on vaccines for dengue fever and outbreak preparedness are currently insufficient. In addition, because there are no appropriate animal models, controversial results from vaccine efficacy assessments and clinical trials have been reported. Therefore, to study the mechanism of dengue fever and test the immunogenicity of vaccines, an appropriate animal model is urgently needed. In addition to mouse models, more suitable models using animals that can be humanized will need to be constructed. In this report, we look at the current status of model animal construction and discuss which models require further development. PMID:28775974

Animal models for dengue vaccine development and testing.

PubMed

Na, Woonsung; Yeom, Minjoo; Choi, Il-Kyu; Yook, Heejun; Song, Daesub

2017-07-01

Dengue fever is a tropical endemic disease; however, because of climate change, it may become a problem in South Korea in the near future. Research on vaccines for dengue fever and outbreak preparedness are currently insufficient. In addition, because there are no appropriate animal models, controversial results from vaccine efficacy assessments and clinical trials have been reported. Therefore, to study the mechanism of dengue fever and test the immunogenicity of vaccines, an appropriate animal model is urgently needed. In addition to mouse models, more suitable models using animals that can be humanized will need to be constructed. In this report, we look at the current status of model animal construction and discuss which models require further development.

The effect of tailor-made additives on crystal growth of methyl paraben: Experiments and modelling

NASA Astrophysics Data System (ADS)

Cai, Zhihui; Liu, Yong; Song, Yang; Guan, Guoqiang; Jiang, Yanbin

2017-03-01

In this study, methyl paraben (MP) was selected as the model component, and acetaminophen (APAP), p-methyl acetanilide (PMAA) and acetanilide (ACET), which share the similar molecular structure as MP, were selected as the three tailor-made additives to study the effect of tailor-made additives on the crystal growth of MP. HPLC results indicated that the MP crystals induced by the three additives contained MP only. Photographs of the single crystals prepared indicated that the morphology of the MP crystals was greatly changed by the additives, but PXRD and single crystal diffraction results illustrated that the MP crystals were the same polymorph only with different crystal habits, and no new crystal form was found compared with other references. To investigate the effect of the additives on the crystal growth, the interaction between additives and facets was discussed in detail using the DFT methods and MD simulations. The results showed that APAP, PMAA and ACET would be selectively adsorbed on the growth surfaces of the crystal facets, which induced the change in MP crystal habits.

Optimal observation network design for conceptual model discrimination and uncertainty reduction

NASA Astrophysics Data System (ADS)

Pham, Hai V.; Tsai, Frank T.-C.

2016-02-01

This study expands the Box-Hill discrimination function to design an optimal observation network to discriminate conceptual models and, in turn, identify a most favored model. The Box-Hill discrimination function measures the expected decrease in Shannon entropy (for model identification) before and after the optimal design for one additional observation. This study modifies the discrimination function to account for multiple future observations that are assumed spatiotemporally independent and Gaussian-distributed. Bayesian model averaging (BMA) is used to incorporate existing observation data and quantify future observation uncertainty arising from conceptual and parametric uncertainties in the discrimination function. In addition, the BMA method is adopted to predict future observation data in a statistical sense. The design goal is to find optimal locations and least data via maximizing the Box-Hill discrimination function value subject to a posterior model probability threshold. The optimal observation network design is illustrated using a groundwater study in Baton Rouge, Louisiana, to collect additional groundwater heads from USGS wells. The sources of uncertainty creating multiple groundwater models are geological architecture, boundary condition, and fault permeability architecture. Impacts of considering homoscedastic and heteroscedastic future observation data and the sources of uncertainties on potential observation areas are analyzed. Results show that heteroscedasticity should be considered in the design procedure to account for various sources of future observation uncertainty. After the optimal design is obtained and the corresponding data are collected for model updating, total variances of head predictions can be significantly reduced by identifying a model with a superior posterior model probability.

Threshold models for genome-enabled prediction of ordinal categorical traits in plant breeding.

PubMed

Montesinos-López, Osval A; Montesinos-López, Abelardo; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo; Eskridge, Kent; Crossa, José

2014-12-23

Categorical scores for disease susceptibility or resistance often are recorded in plant breeding. The aim of this study was to introduce genomic models for analyzing ordinal characters and to assess the predictive ability of genomic predictions for ordered categorical phenotypes using a threshold model counterpart of the Genomic Best Linear Unbiased Predictor (i.e., TGBLUP). The threshold model was used to relate a hypothetical underlying scale to the outward categorical response. We present an empirical application where a total of nine models, five without interaction and four with genomic × environment interaction (G×E) and genomic additive × additive × environment interaction (G×G×E), were used. We assessed the proposed models using data consisting of 278 maize lines genotyped with 46,347 single-nucleotide polymorphisms and evaluated for disease resistance [with ordinal scores from 1 (no disease) to 5 (complete infection)] in three environments (Colombia, Zimbabwe, and Mexico). Models with G×E captured a sizeable proportion of the total variability, which indicates the importance of introducing interaction to improve prediction accuracy. Relative to models based on main effects only, the models that included G×E achieved 9-14% gains in prediction accuracy; adding additive × additive interactions did not increase prediction accuracy consistently across locations. Copyright © 2015 Montesinos-López et al.

A high power, pulsed, microwave amplifier for a synthetique aperture radar electrical model. Phase 1: Design

NASA Astrophysics Data System (ADS)

Atkinson, J. E.; Barker, G. G.; Feltham, S. J.; Gabrielson, S.; Lane, P. C.; Matthews, V. J.; Perring, D.; Randall, J. P.; Saunders, J. W.; Tuck, R. A.

1982-05-01

An electrical model klystron amplifier was designed. Its features include a gridded gun, a single stage depressed collector, a rare earth permanent magnet focusing system, an input loop, six rugged tuners and a coaxial line output section incorporating a coaxial-to-waveguide transducer and a pillbox window. At each stage of the design, the thermal and mechanical aspects were investigated and optimized within the framework of the RF specification. Extensive use was made of data from the preliminary design study and from RF measurements on the breadboard model. In an additional study, a comprehensive draft tube specification has been produced. Great emphasis has been laid on a second additional study on space-qualified materials and processes.

SEMIPARAMETRIC ADDITIVE RISKS REGRESSION FOR TWO-STAGE DESIGN SURVIVAL STUDIES

PubMed Central

Li, Gang; Wu, Tong Tong

2011-01-01

In this article we study a semiparametric additive risks model (McKeague and Sasieni (1994)) for two-stage design survival data where accurate information is available only on second stage subjects, a subset of the first stage study. We derive two-stage estimators by combining data from both stages. Large sample inferences are developed. As a by-product, we also obtain asymptotic properties of the single stage estimators of McKeague and Sasieni (1994) when the semiparametric additive risks model is misspecified. The proposed two-stage estimators are shown to be asymptotically more efficient than the second stage estimators. They also demonstrate smaller bias and variance for finite samples. The developed methods are illustrated using small intestine cancer data from the SEER (Surveillance, Epidemiology, and End Results) Program. PMID:21931467

Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

ERIC Educational Resources Information Center

Zhu, Xiaoshu

2013-01-01

The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

Methodical Approaches to Teaching of Computer Modeling in Computer Science Course

ERIC Educational Resources Information Center

Rakhimzhanova, B. Lyazzat; Issabayeva, N. Darazha; Khakimova, Tiyshtik; Bolyskhanova, J. Madina

2015-01-01

The purpose of this study was to justify of the formation technique of representation of modeling methodology at computer science lessons. The necessity of studying computer modeling is that the current trends of strengthening of general education and worldview functions of computer science define the necessity of additional research of the…

Ultimate strength performance of tankers associated with industry corrosion addition practices

NASA Astrophysics Data System (ADS)

Kim, Do Kyun; Kim, Han Byul; Zhang, Xiaoming; Li, Chen Guang; Paik, Jeom Kee

2014-09-01

In the ship and offshore structure design, age-related problems such as corrosion damage, local denting, and fatigue damage are important factors to be considered in building a reliable structure as they have a significant influence on the residual structural capacity. In shipping, corrosion addition methods are widely adopted in structural design to prevent structural capacity degradation. The present study focuses on the historical trend of corrosion addition rules for ship structural design and investigates their effects on the ultimate strength performance such as hull girder and stiffened panel of double hull oil tankers. Three types of rules based on corrosion addition models, namely historic corrosion rules (pre-CSR), Common Structural Rules (CSR), and harmonised Common Structural Rules (CSRH) are considered and compared with two other corrosion models namely UGS model, suggested by the Union of Greek Shipowners (UGS), and Time-Dependent Corrosion Wastage Model (TDCWM). To identify the general trend in the effects of corrosion damage on the ultimate longitudinal strength performance, the corrosion addition rules are applied to four representative sizes of double hull oil tankers namely Panamax, Aframax, Suezmax, and VLCC. The results are helpful in understanding the trend of corrosion additions for tanker structures

Causal Mediation Analysis of Survival Outcome with Multiple Mediators.

PubMed

Huang, Yen-Tsung; Yang, Hwai-I

2017-05-01

Mediation analyses have been a popular approach to investigate the effect of an exposure on an outcome through a mediator. Mediation models with multiple mediators have been proposed for continuous and dichotomous outcomes. However, development of multimediator models for survival outcomes is still limited. We present methods for multimediator analyses using three survival models: Aalen additive hazard models, Cox proportional hazard models, and semiparametric probit models. Effects through mediators can be characterized by path-specific effects, for which definitions and identifiability assumptions are provided. We derive closed-form expressions for path-specific effects for the three models, which are intuitively interpreted using a causal diagram. Mediation analyses using Cox models under the rare-outcome assumption and Aalen additive hazard models consider effects on log hazard ratio and hazard difference, respectively; analyses using semiparametric probit models consider effects on difference in transformed survival time and survival probability. The three models were applied to a hepatitis study where we investigated effects of hepatitis C on liver cancer incidence mediated through baseline and/or follow-up hepatitis B viral load. The three methods show consistent results on respective effect scales, which suggest an adverse estimated effect of hepatitis C on liver cancer not mediated through hepatitis B, and a protective estimated effect mediated through the baseline (and possibly follow-up) of hepatitis B viral load. Causal mediation analyses of survival outcome with multiple mediators are developed for additive hazard and proportional hazard and probit models with utility demonstrated in a hepatitis study.

Spatial Assessment of Model Errors from Four Regression Techniques

Treesearch

Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove

2005-01-01

Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...

Nonequilibrium radiation and chemistry models for aerocapture vehicle flowfields

NASA Technical Reports Server (NTRS)

Carlson, Leland A.

1991-01-01

The primary tasks performed are: (1) the development of a second order local thermodynamic nonequilibrium (LTNE) model for atoms; (2) the continued development of vibrational nonequilibrium models; and (3) the development of a new multicomponent diffusion model. In addition, studies comparing these new models with previous models and results were conducted and reported.

Mycotoxins co-contamination: Methodological aspects and biological relevance of combined toxicity studies.

PubMed

Alassane-Kpembi, Imourana; Schatzmayr, Gerd; Taranu, Ionelia; Marin, Daniela; Puel, Olivier; Oswald, Isabelle Paule

2017-11-02

Mycotoxins are secondary fungal metabolites produced mainly by Aspergillus, Penicillium, and Fusarium. As evidenced by large-scale surveys, humans and animals are simultaneously exposed to several mycotoxins. Simultaneous exposure could result in synergistic, additive or antagonistic effects. However, most toxicity studies addressed the effects of mycotoxins separately. We present the experimental designs and we discuss the conclusions drawn from in vitro experiments exploring toxicological interactions of mycotoxins. We report more than 80 publications related to mycotoxin interactions. The studies explored combinations involving the regulated groups of mycotoxins, especially aflatoxins, ochratoxins, fumonisins, zearalenone and trichothecenes, but also the "emerging" mycotoxins beauvericin and enniatins. Over 50 publications are based on the arithmetic model of additivity. Few studies used the factorial designs or the theoretical biology-based models of additivity. The latter approaches are gaining increased attention. These analyses allow determination of the type of interaction and, optionally, its magnitude. The type of interaction reported for mycotoxin combinations depended on several factors, in particular cell models and the tested dose ranges. However, synergy among Fusarium toxins was highlighted in several studies. This review indicates that well-addressed in vitro studies remain valuable tools for the screening of interactive potential in mycotoxin mixtures.

A kinetic study of struvite precipitation recycling technology with NaOH/Mg(OH)2 addition.

PubMed

Yu, Rongtai; Ren, Hongqiang; Wang, Yanru; Ding, Lili; Geng, Jingji; Xu, Ke; Zhang, Yan

2013-09-01

Struvite precipitation recycling technology is received wide attention in removal ammonium and phosphate out of wastewater. While past study focused on process efficiency, and less on kinetics. The kinetic study is essential for the design and optimization in the application of struvite precipitation recycling technology. The kinetics of struvite with NaOH/Mg(OH)2 addition were studied by thermogravimetry analysis with three rates (5, 10, 20 °C/min), using Friedman method and Ozawa-Flynn-Wall method, respectively. Degradation process of struvite with NaOH/Mg(OH)2 addition was three steps. The stripping of ammonia from struvite was mainly occurred at the first step. In the first step, the activation energy was about 70 kJ/mol, which has gradually declined as the reaction progress. By model fitting studies, the proper mechanism function for struvite decomposition process with NaOH/Mg(OH)2 addition was revealed. The mechanism function was f(α)=α(α)-(1-α)(n), a Prout-Tompkins nth order (Bna) model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Enhancement of the Mechanical Properties of Basalt Fiber-Wood-Plastic Composites via Maleic Anhydride Grafted High-Density Polyethylene (MAPE) Addition.

PubMed

Chen, Jinxiang; Wang, Yong; Gu, Chenglong; Liu, Jianxun; Liu, Yufu; Li, Min; Lu, Yun

2013-06-18

This study investigated the mechanisms, using microscopy and strength testing approaches, by which the addition of maleic anhydride grafted high-density polyethylene (MAPE) enhances the mechanical properties of basalt fiber-wood-plastic composites (BF-WPCs). The maximum values of the specific tensile and flexural strengths are achieved at a MAPE content of 5%-8%. The elongation increases rapidly at first and then continues slowly. The nearly complete integration of the wood fiber with the high-density polyethylene upon MAPE addition to WPC is examined, and two models of interfacial behavior are proposed. We examined the physical significance of both interfacial models and their ability to accurately describe the effects of MAPE addition. The mechanism of formation of the Model I interface and the integrated matrix is outlined based on the chemical reactions that may occur between the various components as a result of hydrogen bond formation or based on the principle of compatibility, resulting from similar polarity. The Model I fracture occurred on the outer surface of the interfacial layer, visually demonstrating the compatibilization effect of MAPE addition.

Patient-specific in vitro models for hemodynamic analysis of congenital heart disease - Additive manufacturing approach.

PubMed

Medero, Rafael; García-Rodríguez, Sylvana; François, Christopher J; Roldán-Alzate, Alejandro

2017-03-21

Non-invasive hemodynamic assessment of total cavopulmonary connection (TCPC) is challenging due to the complex anatomy. Additive manufacturing (AM) is a suitable alternative for creating patient-specific in vitro models for flow measurements using four-dimensional (4D) Flow MRI. These in vitro systems have the potential to serve as validation for computational fluid dynamics (CFD), simulating different physiological conditions. This study investigated three different AM technologies, stereolithography (SLA), selective laser sintering (SLS) and fused deposition modeling (FDM), to determine differences in hemodynamics when measuring flow using 4D Flow MRI. The models were created using patient-specific MRI data from an extracardiac TCPC. These models were connected to a perfusion pump circulating water at three different flow rates. Data was processed for visualization and quantification of velocity, flow distribution, vorticity and kinetic energy. These results were compared between each model. In addition, the flow distribution obtained in vitro was compared to in vivo. The results showed significant difference in velocities measured at the outlets of the models that required internal support material when printing. Furthermore, an ultrasound flow sensor was used to validate flow measurements at the inlets and outlets of the in vitro models. These results were highly correlated to those measured with 4D Flow MRI. This study showed that commercially available AM technologies can be used to create patient-specific vascular models for in vitro hemodynamic studies at reasonable costs. However, technologies that do not require internal supports during manufacturing allow smoother internal surfaces, which makes them better suited for flow analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structure-related aspects on water diffusivity in fatty acid-soap and skin lipid model systems.

PubMed

Norlén, L; Engblom, J

2000-01-03

Simplified skin barrier models are necessary to get a first hand understanding of the very complex morphology and physical properties of the human skin barrier. In addition, it is of great importance to construct relevant models that will allow for rational testing of barrier perturbing/occlusive effects of a large variety of substances. The primary objective of this work was to study the effect of lipid morphology on water permeation through various lipid mixtures (i.e., partly neutralised free fatty acids, as well as a skin lipid model mixture). In addition, the effects of incorporating Azone((R)) (1-dodecyl-azacycloheptan-2-one) into the skin lipid model mixture was studied. Small- and wide-angle X-ray diffraction was used for structure determinations. It is concluded that: (a) the water flux through a crystalline fatty acid-sodium soap-water mixture (s) is statistically significantly higher than the water flux through the corresponding lamellar (L(alpha)) and reversed hexagonal (H(II)) liquid crystalline phases, which do not differ between themselves; (b) the water flux through mixtures of L(alpha)/s decreases statistically significantly with increasing relative amounts of lamellar (L(alpha)) liquid crystalline phase; (c) the addition of Azone((R)) to a skin lipid model system induces a reduction in water flux. However, further studies are needed to more closely characterise the structural basis for the occlusive effects of Azone((R)) on water flux.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle.

PubMed

Pereira, R J; Bignardi, A B; El Faro, L; Verneque, R S; Vercesi Filho, A E; Albuquerque, L G

2013-01-01

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

USGS Publications Warehouse

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

The Local Ensemble Transform Kalman Filter with the Weather Research and Forecasting Model: Experiments with Real Observations

NASA Astrophysics Data System (ADS)

Miyoshi, Takemasa; Kunii, Masaru

2012-03-01

The local ensemble transform Kalman filter (LETKF) is implemented with the Weather Research and Forecasting (WRF) model, and real observations are assimilated to assess the newly-developed WRF-LETKF system. The WRF model is a widely-used mesoscale numerical weather prediction model, and the LETKF is an ensemble Kalman filter (EnKF) algorithm particularly efficient in parallel computer architecture. This study aims to provide the basis of future research on mesoscale data assimilation using the WRF-LETKF system, an additional testbed to the existing EnKF systems with the WRF model used in the previous studies. The particular LETKF system adopted in this study is based on the system initially developed in 2004 and has been continuously improved through theoretical studies and wide applications to many kinds of dynamical models including realistic geophysical models. Most recent and important improvements include an adaptive covariance inflation scheme which considers the spatial and temporal inhomogeneity of inflation parameters. Experiments show that the LETKF successfully assimilates real observations and that adaptive inflation is advantageous. Additional experiments with various ensemble sizes show that using more ensemble members improves the analyses consistently.

Theory of Planned Behavior including self-stigma and perceived barriers explain help-seeking behavior for sexual problems in Iranian women suffering from epilepsy.

PubMed

Lin, Chung-Ying; Oveisi, Sonia; Burri, Andrea; Pakpour, Amir H

2017-03-01

To apply the Theory of Planned Behavior (TPB) and the two additional concepts self-stigma and perceived barriers to the help-seeking behavior for sexual problems in women with epilepsy. In this 18-month follow-up study, TPB elements, including attitude, subjective norm, perceived behavioral control, and behavioral intention along with self-stigma and perceived barriers in seeking help for sexual problems were assessed in n=818 women with epilepsy (94.0% aged ≤40years). The basic TPB model (model 1) and the TPB model additionally including self-stigma and perceived barriers (Model 2) were analyzed using structural equation modeling (SEM). Both SEM models showed satisfactory model fits. According to model, attitude, subjective norms, perceived behavioral control, and intention explained 63.1% of the variance in help-seeking behavior. Variance was slightly higher (64.5%) when including self-stigma and perceived barriers (model 2). In addition, the fit indices of the models were better highlighting the importance of self-stigma and perceived barriers in help-seeking behavior for sexual problems. Theory of Planned Behavior is useful in explaining help-seeking behavior for sexual problems in women with epilepsy. Self-stigma and perceived barriers are additional factors that should be considered in future interventions aiming to adopt TPB to improve help-seeking behavior for sexual problems. Copyright © 2017 Elsevier Inc. All rights reserved.

Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model

ERIC Educational Resources Information Center

Keiner, Jason F.

2017-01-01

This qualitative case study explored the perceived experiences and outcomes of writing in a hybrid model of instruction in a large suburban high school. In particular, the impact of a hybrid model on the writing process and on future writing performance were examined. In addition, teacher expectation and teacher attitude and their impact upon…

Amino-Acid Network Clique Analysis of Protein Mutation Non-Additive Effects: A Case Study of Lysozme.

PubMed

Ming, Dengming; Chen, Rui; Huang, He

2018-05-10

Optimizing amino-acid mutations in enzyme design has been a very challenging task in modern bio-industrial applications. It is well known that many successful designs often hinge on extensive correlations among mutations at different sites within the enzyme, however, the underpinning mechanism for these correlations is far from clear. Here, we present a topology-based model to quantitively characterize non-additive effects between mutations. The method is based on the molecular dynamic simulations and the amino-acid network clique analysis. It examines if the two mutation sites of a double-site mutation fall into to a 3-clique structure, and associates such topological property of mutational site spatial distribution with mutation additivity features. We analyzed 13 dual mutations of T4 phage lysozyme and found that the clique-based model successfully distinguishes highly correlated or non-additive double-site mutations from those additive ones whose component mutations have less correlation. We also applied the model to protein Eglin c whose structural topology is significantly different from that of T4 phage lysozyme, and found that the model can, to some extension, still identify non-additive mutations from additive ones. Our calculations showed that mutation non-additive effects may heavily depend on a structural topology relationship between mutation sites, which can be quantitatively determined using amino-acid network k -cliques. We also showed that double-site mutation correlations can be significantly altered by exerting a third mutation, indicating that more detailed physicochemical interactions should be considered along with the network clique-based model for better understanding of this elusive mutation-correlation principle.

A novel small animal model to study the replication of simian foamy virus in vivo.

PubMed

Blochmann, Rico; Curths, Christoph; Coulibaly, Cheick; Cichutek, Klaus; Kurth, Reinhard; Norley, Stephen; Bannert, Norbert; Fiebig, Uwe

2014-01-05

Preclinical evaluation in a small animal model would help the development of gene therapies and vaccines based on foamy virus vectors. The establishment of persistent, non-pathogenic infection with the prototype foamy virus in mice and rabbits has been described previously. To extend this spectrum of available animal models, hamsters were inoculated with infectious cell supernatant or bioballistically with a foamy virus plasmid. In addition, a novel foamy virus from a rhesus macaque was isolated and characterised genetically. Hamsters and mice were infected with this new SFVmac isolate to evaluate whether hamsters are also susceptible to infection. Both hamsters and mice developed humoral responses to either virus subtype. Virus integration and replication in different animal tissues were analysed by PCR and co-cultivation. The results strongly indicate establishment of a persistent infection in hamsters. These studies provide a further small animal model for studying FV-based vectors in addition to the established models. © 2013 Elsevier Inc. All rights reserved.

Modelling the average velocity of propagation of the flame front in a gasoline engine with hydrogen additives

NASA Astrophysics Data System (ADS)

Smolenskaya, N. M.; Smolenskii, V. V.

2018-01-01

The paper presents models for calculating the average velocity of propagation of the flame front, obtained from the results of experimental studies. Experimental studies were carried out on a single-cylinder gasoline engine UIT-85 with hydrogen additives up to 6% of the mass of fuel. The article shows the influence of hydrogen addition on the average velocity propagation of the flame front in the main combustion phase. The dependences of the turbulent propagation velocity of the flame front in the second combustion phase on the composition of the mixture and operating modes. The article shows the influence of the normal combustion rate on the average flame propagation velocity in the third combustion phase.

Modification of ginseng flavors by bitter compounds found in chocolate and coffee.

PubMed

Sook Chung, Hee; Lee, Soo-Yeun

2012-06-01

Ginseng is not widely accepted by U.S. consumers due to its unfamiliar flavors, despite its numerous health benefits. Previous studies have suggested that the bitter compounds in chocolate and coffee may mask the off-flavors of ginseng. The objectives of this study were to: (1) profile sensory characteristics of ginseng extract solution, caffeine solution, cyclo (L-Pro-L-Val) solution, theobromine solution, and 2 model solutions simulating chocolate bitterness; and (2) determine the changes in the sensory characteristics of ginseng extract solution by the addition of the bitter compounds found in chocolate and coffee. Thirteen solutions were prepared in concentrations similar to the levels of the bitter compounds found in coffee and chocolate products. Twelve panelists participated in a descriptive analysis panel which included time-intensity ratings. Ginseng extract was characterized as sweeter, starchier, and more green tea than the other sample solutions. Those characteristics of ginseng extract were effectively modified by the addition of caffeine, cyclo (L-Pro-L-Val), and 2 model solutions. A model solution simulating dark chocolate bitterness was the least influenced in intensities of bitterness by the addition of ginseng extract. Results from time-intensity ratings show that the addition of ginseng extract increased duration time in certain bitterness of the 2 model solutions. Bitter compounds found in dark chocolate could be proposed to effectively mask the unique flavors of ginseng. Future studies blending aroma compounds of chocolate and coffee into such model solutions may be conducted to investigate the influence on the perception of the unique flavors through the congruent flavors. © 2012 Institute of Food Technologists®

Psychophysiological interaction between superior temporal gyrus (STG) and cerebellum: An fMRI study

NASA Astrophysics Data System (ADS)

Yusoff, A. N.; Teng, X. L.; Ng, S. B.; Hamid, A. I. A.; Mukari, S. Z. M.

2016-03-01

This study aimed to model the psychophysiological interaction (PPI) between the bilateral STG and cerebellum (lobule VI and lobule VII) during an arithmetic addition task. Eighteen young adults participated in this study. They were instructed to solve single-digit addition tasks in quiet and noisy backgrounds during an fMRI scan. Results showed that in both hemispheres, the response in the cerebellum was found to be linearly influenced by the activity in STG (vice-versa) for both in-quiet and in-noise conditions. However, the influence of the cerebellum on STG seemed to be modulated by noise. A two-way PPI model between STG and cerebellum is suggested. The connectivity between the two regions during a simple addition task in a noisy condition is modulated by the participants’ higher attention to perceive.

Mixed Model Methods for Genomic Prediction and Variance Component Estimation of Additive and Dominance Effects Using SNP Markers

PubMed Central

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005–0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level. PMID:24498162

Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

PubMed

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005-0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level.

Skew-t partially linear mixed-effects models for AIDS clinical studies.

PubMed

Lu, Tao

2016-01-01

We propose partially linear mixed-effects models with asymmetry and missingness to investigate the relationship between two biomarkers in clinical studies. The proposed models take into account irregular time effects commonly observed in clinical studies under a semiparametric model framework. In addition, commonly assumed symmetric distributions for model errors are substituted by asymmetric distribution to account for skewness. Further, informative missing data mechanism is accounted for. A Bayesian approach is developed to perform parameter estimation simultaneously. The proposed model and method are applied to an AIDS dataset and comparisons with alternative models are performed.

Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

2016-12-01

Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over decadal time scales. This suggests that more long-term soil experiments may be necessary to resolve important process uncertainties related to soil C storage. We also suggest future experiments examine how microbial activity responds to warming under a range of soil clay contents and in concert with changes in litter inputs.

Multi-Objective vs. Single Objective Calibration of a Hydrologic Model using Either Different Hydrologic Signatures or Complementary Data Sources

NASA Astrophysics Data System (ADS)

Mai, J.; Cuntz, M.; Zink, M.; Schaefer, D.; Thober, S.; Samaniego, L. E.; Shafii, M.; Tolson, B.

2015-12-01

Hydrologic models are traditionally calibrated against discharge. Recent studies have shown however, that only a few global model parameters are constrained using the integral discharge measurements. It is therefore advisable to use additional information to calibrate those models. Snow pack data, for example, could improve the parametrization of snow-related processes, which might be underrepresented when using only discharge. One common approach is to combine these multiple objectives into one single objective function and allow the use of a single-objective algorithm. Another strategy is to consider the different objectives separately and apply a Pareto-optimizing algorithm. Both methods are challenging in the choice of appropriate multiple objectives with either conflicting interests or the focus on different model processes. A first aim of this study is to compare the two approaches employing the mesoscale Hydrologic Model mHM at several distinct river basins over Europe and North America. This comparison will allow the identification of the single-objective solution on the Pareto front. It is elucidated if this position is determined by the weighting and scaling of the multiple objectives when combing them to the single objective. The principal second aim is to guide the selection of proper objectives employing sensitivity analyses. These analyses are used to determine if an additional information would help to constrain additional model parameters. The additional information are either multiple data sources or multiple signatures of one measurement. It is evaluated if specific discharge signatures can inform different parts of the hydrologic model. The results show that an appropriate selection of discharge signatures increased the number of constrained parameters by more than 50% compared to using only NSE of the discharge time series. It is further assessed if the use of these signatures impose conflicting objectives on the hydrologic model. The usage of signatures is furthermore contrasted to the use of additional observations such as soil moisture or snow height. The gain of using an auxiliary dataset is determined using the parametric sensitivity on the respective modeled variable.

Effects of video modeling on communicative social skills of college students with Asperger syndrome.

PubMed

Mason, Rose A; Rispoli, Mandy; Ganz, Jennifer B; Boles, Margot B; Orr, Kristie

2012-01-01

Empirical support regarding effective interventions for individuals with autism spectrum disorder (ASD) within a postsecondary community is limited. Video modeling, an empirically supported intervention for children and adolescents with ASD, may prove effective in addressing the needs of individuals with ASD in higher education. This study evaluated the effects of video modeling without additional treatment components to improve social-communicative skills, specifically, eye contact, facial expression, and conversational turntaking in college students with ASD. This study utilized a multiple baseline single-case design across behaviors for two post-secondary students with ASD to evaluate the effects of the video modeling intervention. Large effect sizes and statistically significant change across all targeted skills for one participant and eye contact and turntaking for the other participant were obtained. The use of video modeling without additional intervention may increase the social skills of post-secondary students with ASD. Implications for future research are discussed.

Radiation combined injury models to study the effects of interventions and wound biomechanics.

PubMed

Zawaski, Janice A; Yates, Charles R; Miller, Duane D; Kaffes, Caterina C; Sabek, Omaima M; Afshar, Solmaz F; Young, Daniel A; Yang, Yunzhi; Gaber, M Waleed

2014-12-01

In the event of a nuclear detonation, a considerable number of projected casualties will suffer from combined radiation exposure and burn and/or wound injury. Countermeasure assessment in the setting of radiation exposure combined with dermal injury is hampered by a lack of animal models in which the effects of interventions have been characterized. To address this need, we used two separate models to characterize wound closure. The first was an open wound model in mice to study the effect of wound size in combination with whole-body 6 Gy irradiation on the rate of wound closure, animal weight and survival (morbidity). In this model the addition of interventions, wound closure, subcutaneous vehicle injection, topical antiseptic and topical antibiotics were studied to measure their effect on healing and survival. The second was a rat closed wound model to study the biomechanical properties of a healed wound at 10 days postirradiation (irradiated with 6 or 7.5 Gy). In addition, complete blood counts were performed and wound pathology by staining with hematoxylin and eosin, trichrome, CD68 and Ki67. In the mouse open wound model, we found that wound size and morbidity were positively correlated, while wound size and survival were negatively correlated. Regardless of the wound size, the addition of radiation exposure delayed the healing of the wound by approximately 5-6 days. The addition of interventions caused, at a minimum, a 30% increase in survival and improved mean survival by ∼9 days. In the rat closed wound model we found that radiation exposure significantly decreased all wound biomechanical measurements as well as white blood cell, platelet and red blood cell counts at 10 days post wounding. Also, pathological changes showed a loss of dermal structure, thickening of dermis, loss of collagen/epithelial hyperplasia and an increased density of macrophages. In conclusion, we have characterized the effect of a changing wound size in combination with radiation exposure. We also demonstrated that the most effective interventions mitigated insensible fluid loss, which could help to define the most appropriate requirements of a successful countermeasure.

Interrelations between different canonical descriptions of dissipative systems

NASA Astrophysics Data System (ADS)

Schuch, D.; Guerrero, J.; López-Ruiz, F. F.; Aldaya, V.

2015-04-01

There are many approaches for the description of dissipative systems coupled to some kind of environment. This environment can be described in different ways; only effective models are being considered here. In the Bateman model, the environment is represented by one additional degree of freedom and the corresponding momentum. In two other canonical approaches, no environmental degree of freedom appears explicitly, but the canonical variables are connected with the physical ones via non-canonical transformations. The link between the Bateman approach and those without additional variables is achieved via comparison with a canonical approach using expanding coordinates, as, in this case, both Hamiltonians are constants of motion. This leads to constraints that allow for the elimination of the additional degree of freedom in the Bateman approach. These constraints are not unique. Several choices are studied explicitly, and the consequences for the physical interpretation of the additional variable in the Bateman model are discussed.

Coping with Relationship Stressors: The Impact of Different Working Models of Attachment and Links to Adaptation

ERIC Educational Resources Information Center

Seiffge-Krenke, Inge

2006-01-01

The study explores the role of working models of attachment in the process of coping with relationship stressors with a focus on long-term adaptation. In a 7-year longitudinal study of 112 participants, stress and coping were assessed during adolescence and emerging adulthood. In addition, working models of attachment were assessed by employing…

Modeling the erythemal surface diffuse irradiance fraction for Badajoz, Spain

NASA Astrophysics Data System (ADS)

Sanchez, Guadalupe; Serrano, Antonio; Cancillo, María Luisa

2017-10-01

Despite its important role on the human health and numerous biological processes, the diffuse component of the erythemal ultraviolet irradiance (UVER) is scarcely measured at standard radiometric stations and therefore needs to be estimated. This study proposes and compares 10 empirical models to estimate the UVER diffuse fraction. These models are inspired from mathematical expressions originally used to estimate total diffuse fraction, but, in this study, they are applied to the UVER case and tested against experimental measurements. In addition to adapting to the UVER range the various independent variables involved in these models, the total ozone column has been added in order to account for its strong impact on the attenuation of ultraviolet radiation. The proposed models are fitted to experimental measurements and validated against an independent subset. The best-performing model (RAU3) is based on a model proposed by Ruiz-Arias et al. (2010) and shows values of r2 equal to 0.91 and relative root-mean-square error (rRMSE) equal to 6.1 %. The performance achieved by this entirely empirical model is better than those obtained by previous semi-empirical approaches and therefore needs no additional information from other physically based models. This study expands on previous research to the ultraviolet range and provides reliable empirical models to accurately estimate the UVER diffuse fraction.

Modeling and experimental studies on intermittent starch feeding and citrate addition in simultaneous saccharification and fermentation of starch to flavor compounds.

PubMed

Chavan, Abhijit R; Raghunathan, Anuradha; Venkatesh, K V

2009-04-01

Simultaneous saccharification and fermentation (SSF) is a combined process of saccharification of a renewable bioresource and fermentation process to produce products, such as lactic acid and ethanol. Recently, SSF has been extensively used to convert various sources of cellulose and starch into fermentative products. Here, we present a study on production of buttery flavors, namely diacetyl and acetoin, by growing Lactobacillus rhamnosus on a starch medium containing the enzyme glucoamylase. We further develop a structured kinetics for the SSF process, which includes enzyme and growth kinetics. The model was used to simulate the effect of pH and temperature on the SSF process so as to obtain optimum operating conditions. The model was experimentally verified by conducting SSF using an initial starch concentration of 100 g/L. The study demonstrated that the developed kinetic was able to suggest strategies for improved productivities. The developed model was able to accurately predict the enhanced productivity of flavors in a three stage process with intermittent addition of starch. Experimental and simulations demonstrated that citrate addition can also lead to enhanced productivity of flavors. The developed optimal model for SSF was able to capture the dynamics of SSF in batch mode as well as in a three stage process. The structured kinetics was also able to quantify the effect of multiple substrates present in the medium. The study demonstrated that structured kinetic models can be used in the future for design and optimization of SSF as a batch or a fed-batch process.

Effects of build parameters on linear wear loss in plastic part produced by fused deposition modeling

NASA Astrophysics Data System (ADS)

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2017-07-01

Fused Deposition Modeling (FDM) is one of the prominent additive manufacturing technologies for producing polymer products. FDM is a complex additive manufacturing process that can be influenced by many process conditions. The industrial demands required from the FDM process are increasing with higher level product functionality and properties. The functionality and performance of FDM manufactured parts are greatly influenced by the combination of many various FDM process parameters. Designers and researchers always pay attention to study the effects of FDM process parameters on different product functionalities and properties such as mechanical strength, surface quality, dimensional accuracy, build time and material consumption. However, very limited studies have been carried out to investigate and optimize the effect of FDM build parameters on wear performance. This study focuses on the effect of different build parameters on micro-structural and wear performance of FDM specimens using definitive screening design based quadratic model. This would reduce the cost and effort of additive manufacturing engineer to have a systematic approachto make decision among the manufacturing parameters to achieve the desired product quality.

Growth morphologies of wax in the presence of kinetic inhibitors

NASA Astrophysics Data System (ADS)

Tetervak, Alexander A.

Driven by the need to prevent crystallization of normal alkanes from diesel fuels in cold climates, the petroleum industry has developed additives to slow the growth of these crystals and alter their morphologies. Although the utility of these kinetic inhibitors has been well demonstrated in the field, few studies have directly monitored their effect at microscopic morphology, and the mechanisms by which they act remain poorly understood. Here we present a study of the effects of such additives on the crystallization of long-chain n-alkanes from solution. The additives change the growth morphology from plate-like crystals to a microcrystalline mesh. When we impose a front velocity by moving the sample through a temperature gradient, the mesh growth may form a macroscopic banded pattern and also exhibit a burst-crystallization behavior. In this study, we characterize these crystallization phenomena and also two growth models: a continuum model that demonstrates the essential behavior of the banded crystallization, and a simple qualitative cellular automata model that captures basics of the burst-crystallization process. Keywords: solidification; mesh crystallization; kinetic inhibitor; burst growth.

A twin study of specific bulimia nervosa symptoms.

PubMed

Mazzeo, S E; Mitchell, K S; Bulik, C M; Aggen, S H; Kendler, K S; Neale, M C

2010-07-01

Twin studies have suggested that additive genetic factors significantly contribute to liability to bulimia nervosa (BN). However, the diagnostic criteria for BN remain controversial. In this study, an item-factor model was used to examine the BN diagnostic criteria and the genetic and environmental contributions to BN in a population-based twin sample. The validity of the equal environment assumption (EEA) for BN was also tested. Participants were 1024 female twins (MZ n=614, DZ n=410) from the population-based Mid-Atlantic Twin Registry. BN was assessed using symptom-level (self-report) items consistent with DSM-IV and ICD-10 diagnostic criteria. Items assessing BN were included in an item-factor model. The EEA was measured by items assessing similarity of childhood and adolescent environment, which have demonstrated construct validity. Scores on the EEA factor were used to specify the degree to which twins shared environmental experiences in this model. The EEA was not violated for BN. Modeling results indicated that the majority of the variance in BN was due to additive genetic factors. There was substantial variability in additive genetic and environmental contributions to specific BN symptoms. Most notably, vomiting was very strongly influenced by additive genetic factors, while other symptoms were much less heritable, including the influence of weight on self-evaluation. These results highlight the importance of assessing eating disorders at the symptom level. Refinement of eating disorder phenotypes could ultimately lead to improvements in treatment and targeted prevention, by clarifying sources of variation for specific components of symptomatology.

Meta-Analysis of the Minimalist Training Model

ERIC Educational Resources Information Center

Ginns, Paul; Hollender, Nina; Reimann, Peter

2006-01-01

This article reviews research on the Minimalist instructional design model, a learner-centred approach to the design of instructional materials such as computer program manuals or on-line help. Studies in this paradigm have typically compared minimalist materials against traditional "system-centred" materials. Additionally, some studies have…

Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

PubMed

Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

2014-04-02

The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

Digestion of starch in a dynamic small intestinal model.

PubMed

Jaime-Fonseca, M R; Gouseti, O; Fryer, P J; Wickham, M S J; Bakalis, S

2016-12-01

The rate and extent of starch digestion have been linked with important health aspects, such as control of obesity and type-2 diabetes. In vitro techniques are often used to study digestion and simulated nutrient absorption; however, the effect of gut motility is often disregarded. The present work aims at studying fundamentals of starch digestion, e.g. the effect of viscosity on digestibility, taking into account both biochemical and engineering (gut motility) parameters. New small intestinal model (SIM) that realistically mimics gut motility (segmentation) was used to study digestibility and simulated oligosaccharide bio accessibility of (a) model starch solutions; (b) bread formulations. First, the model was compared with the rigorously mixed stirred tank reactor (STR). Then the effects of enzyme concentration/flow rate, starch concentration, and digesta viscosity (addition of guar gum) were evaluated. Compared to the STR, the SIM showed presence of lag phase when no digestive processes could be detected. The effects of enzyme concentration and flow rate appeared to be marginal in the region of mass transfer limited reactions. Addition of guar gum reduced simulated glucose absorption by up to 45 % in model starch solutions and by 35 % in bread formulations, indicating the importance of chyme rheology on nutrient bioaccessibility. Overall, the work highlights the significance of gut motility in digestive processes and offers a powerful tool in nutritional studies that, additionally to biochemical, considers engineering aspects of digestion. The potential to modulate food digestibility and nutrient bioaccessibility by altering food formulation is indicated.

Enhancement of the Mechanical Properties of Basalt Fiber-Wood-Plastic Composites via Maleic Anhydride Grafted High-Density Polyethylene (MAPE) Addition

PubMed Central

Chen, Jinxiang; Wang, Yong; Gu, Chenglong; Liu, Jianxun; Liu, Yufu; Li, Min; Lu, Yun

2013-01-01

This study investigated the mechanisms, using microscopy and strength testing approaches, by which the addition of maleic anhydride grafted high-density polyethylene (MAPE) enhances the mechanical properties of basalt fiber-wood-plastic composites (BF-WPCs). The maximum values of the specific tensile and flexural strengths areachieved at a MAPE content of 5%–8%. The elongation increases rapidly at first and then continues slowly. The nearly complete integration of the wood fiber with the high-density polyethylene upon MAPE addition to WPC is examined, and two models of interfacial behavior are proposed. We examined the physical significance of both interfacial models and their ability to accurately describe the effects of MAPE addition. The mechanism of formation of the Model I interface and the integrated matrix is outlined based on the chemical reactions that may occur between the various components as a result of hydrogen bond formation or based on the principle of compatibility, resulting from similar polarity. The Model I fracture occurred on the outer surface of the interfacial layer, visually demonstrating the compatibilization effect of MAPE addition. PMID:28809285

Teaching Facts of Addition to Brazilian Children with Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Costa, Adriana Corrêa; Rohde, Luis Augusto; Dorneles, Beatriz Vargas

2015-01-01

Storage and/or automatic retrieval of the basic facts of addition from the long-term memory seems to be impaired in children with ADHD presenting arithmetical difficulties. The present study was carried out to evaluate the effectiveness of an educational intervention model designed to teach basic facts of addition as a means of advancing from…

Whole-Motion Model of Perception during Forward- and Backward-Facing Centrifuge Runs

PubMed Central

Holly, Jan E.; Vrublevskis, Arturs; Carlson, Lindsay E.

2009-01-01

Illusory perceptions of motion and orientation arise during human centrifuge runs without vision. Asymmetries have been found between acceleration and deceleration, and between forward-facing and backward-facing runs. Perceived roll tilt has been studied extensively during upright fixed-carriage centrifuge runs, and other components have been studied to a lesser extent. Certain, but not all, perceptual asymmetries in acceleration-vs-deceleration and forward-vs-backward motion can be explained by existing analyses. The immediate acceleration-deceleration roll-tilt asymmetry can be explained by the three-dimensional physics of the external stimulus; in addition, longer-term data has been modeled in a standard way using physiological time constants. However, the standard modeling approach is shown in the present research to predict forward-vs-backward-facing symmetry in perceived roll tilt, contradicting experimental data, and to predict perceived sideways motion, rather than forward or backward motion, around a curve. The present work develops a different whole-motion-based model taking into account the three-dimensional form of perceived motion and orientation. This model predicts perceived forward or backward motion around a curve, and predicts additional asymmetries such as the forward-backward difference in roll tilt. This model is based upon many of the same principles as the standard model, but includes an additional concept of familiarity of motions as a whole. PMID:19208962

Flood damage estimation of companies: A comparison of Stage-Damage-Functions and Random Forests

NASA Astrophysics Data System (ADS)

Sieg, Tobias; Kreibich, Heidi; Vogel, Kristin; Merz, Bruno

2017-04-01

The development of appropriate flood damage models plays an important role not only for the damage assessment after an event but also to develop adaptation and risk mitigation strategies. So called Stage-Damage-Functions (SDFs) are often applied as a standard approach to estimate flood damage. These functions assign a certain damage to the water depth depending on the use or other characteristics of the exposed objects. Recent studies apply machine learning algorithms like Random Forests (RFs) to model flood damage. These algorithms usually consider more influencing variables and promise to depict a more detailed insight into the damage processes. In addition they provide an inherent validation scheme. Our study focuses on direct, tangible damage of single companies. The objective is to model and validate the flood damage suffered by single companies with SDFs and RFs. The data sets used are taken from two surveys conducted after the floods in the Elbe and Danube catchments in the years 2002 and 2013 in Germany. Damage to buildings (n = 430), equipment (n = 651) as well as goods and stock (n = 530) are taken into account. The model outputs are validated via a comparison with the actual flood damage acquired by the surveys and subsequently compared with each other. This study investigates the gain in model performance with the use of additional data and the advantages and disadvantages of the RFs compared to SDFs. RFs show an increase in model performance with an increasing amount of data records over a comparatively large range, while the model performance of the SDFs is already saturated for a small set of records. In addition, the RFs are able to identify damage influencing variables, which improves the understanding of damage processes. Hence, RFs can slightly improve flood damage predictions and provide additional insight into the underlying mechanisms compared to SDFs.

Functional Generalized Additive Models.

PubMed

McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David

2014-01-01

We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F { X ( t ), t } where F (·,·) is an unknown regression function and X ( t ) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F (·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X ( t ) is a signal from diffusion tensor imaging at position, t , along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online.

Electrostatic Levitation for Studies of Additive Manufactured Materials

NASA Technical Reports Server (NTRS)

SanSoucie, Michael P.; Rogers, Jan R.; Tramel, Terri

2014-01-01

The electrostatic levitation (ESL) laboratory at NASA's Marshall Space Flight Center is a unique facility for investigators studying high temperature materials. The laboratory boasts two levitators in which samples can be levitated, heated, melted, undercooled, and resolidified. Electrostatic levitation minimizes gravitational effects and allows materials to be studied without contact with a container or instrumentation. The lab also has a high temperature emissivity measurement system, which provides normal spectral and normal total emissivity measurements at use temperature. The ESL lab has been instrumental in many pioneering materials investigations of thermophysical properties, e.g., creep measurements, solidification, triggered nucleation, and emissivity at high temperatures. Research in the ESL lab has already led to the development of advanced high temperature materials for aerospace applications, coatings for rocket nozzles, improved medical and industrial optics, metallic glasses, ablatives for reentry vehicles, and materials with memory. Modeling of additive manufacturing materials processing is necessary for the study of their resulting materials properties. In addition, the modeling of the selective laser melting processes and its materials property predictions are also underway. Unfortunately, there is very little data for the properties of these materials, especially of the materials in the liquid state. Some method to measure thermophysical properties of additive manufacturing materials is necessary. The ESL lab is ideal for these studies. The lab can provide surface tension and viscosity of molten materials, density measurements, emissivity measurements, and even creep strength measurements. The ESL lab can also determine melting temperature, surface temperatures, and phase transition temperatures of additive manufactured materials. This presentation will provide background on the ESL lab and its capabilities, provide an approach to using the ESL in supporting the development and modeling of the selective laser melting process for metals, and provide an overview of the results to date.

Modeling influence of tide stages on forecasts of the 2010 Chilean tsunami

NASA Astrophysics Data System (ADS)

Uslu, B. U.; Chamberlin, C.; Walsh, D.; Eble, M. C.

2010-12-01

The impact of the 2010 Chilean tsunami is studied using the NOAA high-resolution tsunami forecast model augmented to include modeled tide heights in addition to deep-water tsunami propagation as boundary-condition input. The Chilean tsunami was observed at the Los Angeles tide station at mean low water, Hilo at low, Pago Pago at mid tide and Wake Island near high tide. Because the tsunami arrived at coastal communities at a representative variety of tide stages, 2010 Chile tsunami provides opportunity to study the tsunami impacts at different tide levels to different communities. The current forecast models are computed with a constant tidal stage, and this study evaluates techniques for adding an additional varying predicted tidal component in a forecasting context. Computed wave amplitudes, wave currents and flooding are compared at locations around the Pacific, and the difference in tsunami impact due to tidal stage is studied. This study focuses on how tsunami impacts vary with different tide levels, and helps us understand how the inclusion of tidal components can improve real-time forecast accuracy.

Modeling and Predicting the Stress Relaxation of Composites with Short and Randomly Oriented Fibers

PubMed Central

Obaid, Numaira; Sain, Mohini

2017-01-01

The addition of short fibers has been experimentally observed to slow the stress relaxation of viscoelastic polymers, producing a change in the relaxation time constant. Our recent study attributed this effect of fibers on stress relaxation behavior to the interfacial shear stress transfer at the fiber-matrix interface. This model explained the effect of fiber addition on stress relaxation without the need to postulate structural changes at the interface. In our previous study, we developed an analytical model for the effect of fully aligned short fibers, and the model predictions were successfully compared to finite element simulations. However, in most industrial applications of short-fiber composites, fibers are not aligned, and hence it is necessary to examine the time dependence of viscoelastic polymers containing randomly oriented short fibers. In this study, we propose an analytical model to predict the stress relaxation behavior of short-fiber composites where the fibers are randomly oriented. The model predictions were compared to results obtained from Monte Carlo finite element simulations, and good agreement between the two was observed. The analytical model provides an excellent tool to accurately predict the stress relaxation behavior of randomly oriented short-fiber composites. PMID:29053601

Collaborative Research: failure of RockMasses from Nucleation and Growth of Microscopic Defects and Disorder

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, William

Over the 21 years of funding we have pursued several projects related to earthquakes, damage and nucleation. We developed simple models of earthquake faults which we studied to understand Gutenburg-Richter scaling, foreshocks and aftershocks, the effect of spatial structure of the faults and its interaction with underlying self organization and phase transitions. In addition we studied the formation of amorphous solids via the glass transition. We have also studied nucleation with a particular concentration on transitions in systems with a spatial symmetry change. In addition we investigated the nucleation process in models that mimic rock masses. We obtained the structuremore » of the droplet in both homogeneous and heterogeneous nucleation. We also investigated the effect of defects or asperities on the nucleation of failure in simple models of earthquake faults.« less

Additive hazards regression and partial likelihood estimation for ecological monitoring data across space.

PubMed

Lin, Feng-Chang; Zhu, Jun

2012-01-01

We develop continuous-time models for the analysis of environmental or ecological monitoring data such that subjects are observed at multiple monitoring time points across space. Of particular interest are additive hazards regression models where the baseline hazard function can take on flexible forms. We consider time-varying covariates and take into account spatial dependence via autoregression in space and time. We develop statistical inference for the regression coefficients via partial likelihood. Asymptotic properties, including consistency and asymptotic normality, are established for parameter estimates under suitable regularity conditions. Feasible algorithms utilizing existing statistical software packages are developed for computation. We also consider a simpler additive hazards model with homogeneous baseline hazard and develop hypothesis testing for homogeneity. A simulation study demonstrates that the statistical inference using partial likelihood has sound finite-sample properties and offers a viable alternative to maximum likelihood estimation. For illustration, we analyze data from an ecological study that monitors bark beetle colonization of red pines in a plantation of Wisconsin.

Socioeconomic status and parenting in ethnic minority families: testing a minority family stress model.

PubMed

Emmen, Rosanneke A G; Malda, Maike; Mesman, Judi; van Ijzendoorn, Marinus H; Prevoo, Mariëlle J L; Yeniad, Nihal

2013-12-01

According to the family stress model (Conger & Donnellan, 2007), low socioeconomic status (SES) predicts less-than-optimal parenting through family stress. Minority families generally come from lower SES backgrounds than majority families, and may experience additional stressors associated with their minority status, such as acculturation stress. The primary goal of this study was to test a minority family stress model with a general family stress pathway, as well as a pathway specific to ethnic minority families. The sample consisted of 107 Turkish-Dutch mothers and their 5- to 6-year-old children, and positive parenting was observed during a 7-min problem-solving task. In addition, mothers reported their daily hassles, psychological distress, and acculturation stress. The relation between SES and positive parenting was partially mediated by both general maternal psychological stress and maternal acculturation stress. Our study contributes to the argument that stressors specific to minority status should be considered in addition to more general demographic and family stressors in understanding parenting behavior in ethnic minority families.

Studying Parental Involvement and University Access and Choice: An "Interacting Multiple Capitals" Model

ERIC Educational Resources Information Center

Gao, Fang; Ng, Jacky Chi Kit

2017-01-01

Capital-embedded parental involvement in education is essential in enhancing university enrolment and maximising the educational potentials for equality and excellence. Previous studies in this field have mainly utilised Perna's (2000, 2006) model, which defines parental involvement as social capital and identifies the additive influences of…

Developing and Modeling 21st-Century Skills with Preservice Teachers

ERIC Educational Resources Information Center

Urbani, Jacquelyn M.; Roshandel, Shadi; Michaels, Rosemarie; Truesdell, Elizabeth

2017-01-01

This study describes a collaboration in one northern California university between three teacher education programs (multiple subject, single subject, and education specialist) that explores how and to what extent faculty are developing and modeling the 21st-century skills in preservice teachers. In addition, this study analyzes preservice…

NB-PLC channel modelling with cyclostationary noise addition & OFDM implementation for smart grid

NASA Astrophysics Data System (ADS)

Thomas, Togis; Gupta, K. K.

2016-03-01

Power line communication (PLC) technology can be a viable solution for the future ubiquitous networks because it provides a cheaper alternative to other wired technology currently being used for communication. In smart grid Power Line Communication (PLC) is used to support communication with low rate on low voltage (LV) distribution network. In this paper, we propose the channel modelling of narrowband (NB) PLC in the frequency range 5 KHz to 500 KHz by using ABCD parameter with cyclostationary noise addition. Behaviour of the channel was studied by the addition of 11KV/230V transformer, by varying load location and load. Bit error rate (BER) Vs signal to noise ratio SNR) was plotted for the proposed model by employing OFDM. Our simulation results based on the proposed channel model show an acceptable performance in terms of bit error rate versus signal to noise ratio, which enables communication required for smart grid applications.

Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

PubMed Central

Bouvet, J-M; Makouanzi, G; Cros, D; Vigneron, Ph

2016-01-01

Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information. PMID:26328760

A Meta-Analysis of Video-Modeling Based Interventions for Reduction of Challenging Behaviors for Students with EBD

ERIC Educational Resources Information Center

Losinski, Mickey; Wiseman, Nicole; White, Sherry A.; Balluch, Felicity

2016-01-01

The current study examined the use of video modeling (VM)-based interventions to reduce the challenging behaviors of students with emotional or behavioral disorders. Each study was evaluated using Council for Exceptional Children's (CEC's) quality indicators for evidence-based practices. In addition, study effects were calculated along the three…

Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis.

PubMed

Enden, T; Resch, S; White, C; Wik, H S; Kløw, N E; Sandset, P M

2013-06-01

Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64,709 for additional CDT and $51,866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20,429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55,000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50,000/QALY gained. Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. © 2013 International Society on Thrombosis and Haemostasis.

Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis

PubMed Central

ENDEN, T.; RESCH, S.; WHITE, C.; WIK, H. S.; KLØW, N. E.; SANDSET, P. M.

2013-01-01

Summary Background Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). Objectives To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Methods Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). Results In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64 709 for additional CDT and $51 866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20 429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55 000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50 000/QALY gained. Conclusions Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. PMID:23452204

Prototype Willingness Model Drinking Cognitions Mediate Personalized Normative Feedback Efficacy.

PubMed

Lewis, Melissa A; Litt, Dana M; Tomkins, Mary; Neighbors, Clayton

2017-05-01

Personalized normative feedback (PNF) interventions have been shown to be efficacious at reducing college student drinking. Because descriptive norms have been shown to mediate PNF efficacy, the current study focused on examining additional prototype willingness model social reaction cognitions, namely, prototypes and willingness, as mediators of intervention efficacy. We expected the PNF interventions to be associated with increased prototype favorability of students who do not drink, which would in turn be associated with decreased willingness to drink and subsequently, less drinking. The current study included 622 college students (53.2% women; 62% Caucasian) who reported one or more heavy drinking episodes in the past month and completed baseline and three-month follow-up assessments. As posited by the framework of the prototype willingness model, sequential mediation analyses were conducted to evaluate increases in abstainer prototype favorability on willingness on drinking, and subsequently willingness to drink on drinking behavior. Mediation results revealed significant indirect effects of PNF on three-month drinking through three-month prototypes and willingness, indicating that the social reaction pathway of the prototype willingness model was supported. Findings have important implications for PNF interventions aiming to reduce high-risk drinking among college students. Study findings suggest that we should consider looking at additional socially-based mediators of PNF efficacy in addition to perceived descriptive norms.

Prototype Willingness Model Drinking Cognitions Mediate Personalized Normative Feedback Efficacy

PubMed Central

Litt, Dana M.; Tomkins, Mary; Neighbors, Clayton

2017-01-01

Personalized normative feedback (PNF) interventions have been shown to be efficacious at reducing college student drinking. Because descriptive norms have been shown to mediate PNF efficacy, the current study focused on examining additional prototype willingness model social reaction cognitions, namely, prototypes and willingness, as mediators of intervention efficacy. We expected the PNF interventions to be associated with increased prototype favorability of students who do not drink, which would in turn be associated with decreased willingness to drink and subsequently, less drinking. The current study included 622 college students (53.2% women; 62% Caucasian) who reported one or more heavy drinking episodes in the past month and completed baseline and three-month follow-up assessments. As posited by the framework of the prototype willingness model, sequential mediation analyses were conducted to evaluate increases in abstainer prototype favorability on willingness on drinking, and subsequently willingness to drink on drinking behavior. Mediation results revealed significant indirect effects of PNF on three-month drinking through three-month prototypes and willingness, indicating that the social reaction pathway of the prototype willingness model was supported. Findings have important implications for PNF interventions aiming to reduce high-risk drinking among college students. Study findings suggest that we should consider looking at additional socially-based mediators of PNF efficacy in addition to perceived descriptive norms. PMID:27995431

Investigating melting induced mantle heterogeneities in plate driven mantle convection models

NASA Astrophysics Data System (ADS)

Price, M.; Davies, H.; Panton, J.

2017-12-01

Observations from geochemistry and seismology continue to suggest a range of complex heterogeneity in Earth's mantle. In the deep mantle, two large low velocity provinces (LLVPs) have been regularly observed in seismic studies, with their longevity, composition and density compared to the surrounding mantle debated. The cause of these observed LLVPs is equally uncertain, with previous studies advocating either thermal or thermo-chemical causes. There is also evidence that these structures could provide chemically distinct reservoirs within the mantle, with recent studies also suggesting there may be additional reservoirs in the mantle, such as bridgmanite-enriched ancient mantle structures (BEAMS). One way to test these hypotheses is using computational models of the mantle, with models that capture the full 3D system being both complex and computationally expensive. Here we present results from our global mantle model TERRA. Using our model, we can track compositional variations in the convecting mantle that are generated by self-consistent, evolving melting zones. Alongside the melting, we track trace elements and other volatiles which can be partitioned during melting events, and expelled and recycled at the surface. Utilising plate reconstruction models as a boundary condition, the models generate the tectonic features observed at Earth's surface, while also organising the lower mantle into recognisable degree-two structures. This results in our models generating basaltic `oceanic' crusts which are then brought into the mantle at tectonic boundaries, providing additional chemical heterogeneity in the mantle volume. Finally, by utilising thermodynamic lookup tables to convert the final outputs from the model to seismic structures, together with resolution filters for global tomography models, we are able to make direct comparisons between our results and observations. By varying the parameters of the model, we investigate a range of current hypotheses for heterogeneity in the mantle. Our work attempts to reconcile the many proposed current ideas for the deep mantle, giving additional insight from modelling on the latest observations from other Deep Earth disciplines.

Evaluation of a Mathematical Model of Rat Body Weight Regulation in Application to Caloric Restriction and Drug Treatment Studies.

PubMed

Selimkhanov, Jangir; Thompson, W Clayton; Patterson, Terrell A; Hadcock, John R; Scott, Dennis O; Maurer, Tristan S; Musante, Cynthia J

2016-01-01

The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra) study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology.

Evaluation of a Mathematical Model of Rat Body Weight Regulation in Application to Caloric Restriction and Drug Treatment Studies

PubMed Central

Selimkhanov, Jangir; Patterson, Terrell A.; Scott, Dennis O.; Maurer, Tristan S.; Musante, Cynthia J.

2016-01-01

The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra) study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology. PMID:27227543

Septic tank additive impacts on microbial populations.

PubMed

Pradhan, S; Hoover, M T; Clark, G H; Gumpertz, M; Wollum, A G; Cobb, C; Strock, J

2008-01-01

Environmental health specialists, other onsite wastewater professionals, scientists, and homeowners have questioned the effectiveness of septic tank additives. This paper describes an independent, third-party, field scale, research study of the effects of three liquid bacterial septic tank additives and a control (no additive) on septic tank microbial populations. Microbial populations were measured quarterly in a field study for 12 months in 48 full-size, functioning septic tanks. Bacterial populations in the 48 septic tanks were statistically analyzed with a mixed linear model. Additive effects were assessed for three septic tank maintenance levels (low, intermediate, and high). Dunnett's t-test for tank bacteria (alpha = .05) indicated that none of the treatments were significantly different, overall, from the control at the statistical level tested. In addition, the additives had no significant effects on septic tank bacterial populations at any of the septic tank maintenance levels. Additional controlled, field-based research iswarranted, however, to address additional additives and experimental conditions.

Longitudinal changes in health-related quality of life for chronic diseases: an example in hemophilia A.

PubMed

Poon, Jiat-Ling; Doctor, Jason N; Nichol, Michael B

2014-08-01

Patients with well-managed rare chronic diseases such as hemophilia maintain a stable health state and health-related quality of life (HrQoL) that may be affected by acute events. Longitudinal HrQoL assessments analyzed using multivariate multilevel (MVML) modelling can determine the impact of such events on individuals (within-person effect) and identify factors influencing within-population differences (between-person effect). To demonstrate the application of MVML modelling in a longitudinal study of HrQoL in hemophilia A. Using data on 136 adults and 125 children from a two-year observational cohort study of burden of illness in US hemophilia A patients, MVML modelling determined the effect of time-invariant (sociodemographic and clinical characteristics) and time-varying factors (bleeding frequency, emergency room visits, and missed work/school days) on within-person and between-person HrQoL changes. HrQoL was assessed using the SF-12 health survey (adults) and PedsQL inventory (children) at baseline, then every 6 months. In children, within-person (p < 0.0001) and between-person (p < 0.0001) psychosocial functioning was reduced by each additional bleed and missed day (within-person: p = 0.0089; between-person: p = 0.0060). Within-person physical functioning was reduced by each additional bleed (p < 0.0001), emergency room (ER) visit (p = 0.0284), and missed day (p = 0.0473). Between-persons, additional missed days (p < 0.0001) significantly decreased physical functioning. In adults, each additional missed day reduced SF-12 Health Survey mental (p = 0.0025) and physical (p = 0.0093) component summary scores. Each additional bleed also decreased physical component summary (PCS) significantly (p = 0.0093). This study demonstrated the applicability of MVML modelling in identifying time-invariant and time-varying factors influencing HrQoL in a rare chronic disease population. Small but significant within-person and between-person changes in HrQoL with each additional acute event experienced were identified, which if frequent, could have a large cumulative impact. The results suggest that MVML modelling may be applied to future studies of longitudinal change in HrQoL in other rare chronic disease populations.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

The Dynamics of School Change: Response to the Article "Comer's School Development Program in Prince George's Count, Maryland: A Theory-based Evaluation," by Thomas D. Cook et al.

ERIC Educational Resources Information Center

Comer, James P.; Haynes, Norris M.

1999-01-01

Comments on a study of Comer's School Development Model, indicating that the study, as conducted, was not a study of the model but a limited study of the effects of one application of the model's process. In addition, the evaluation was carried out over only 2 years for each group, when experience shows that at least 3 years are necessary to show…

Strengthen forensic entomology in court--the need for data exploration and the validation of a generalised additive mixed model.

PubMed

Baqué, Michèle; Amendt, Jens

2013-01-01

Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.

Bayesian Inference for the Stereotype Regression Model: Application to a Case-control Study of Prostate Cancer

PubMed Central

Ahn, Jaeil; Mukherjee, Bhramar; Banerjee, Mousumi; Cooney, Kathleen A.

2011-01-01

Summary The stereotype regression model for categorical outcomes, proposed by Anderson (1984) is nested between the baseline category logits and adjacent category logits model with proportional odds structure. The stereotype model is more parsimonious than the ordinary baseline-category (or multinomial logistic) model due to a product representation of the log odds-ratios in terms of a common parameter corresponding to each predictor and category specific scores. The model could be used for both ordered and unordered outcomes. For ordered outcomes, the stereotype model allows more flexibility than the popular proportional odds model in capturing highly subjective ordinal scaling which does not result from categorization of a single latent variable, but are inherently multidimensional in nature. As pointed out by Greenland (1994), an additional advantage of the stereotype model is that it provides unbiased and valid inference under outcome-stratified sampling as in case-control studies. In addition, for matched case-control studies, the stereotype model is amenable to classical conditional likelihood principle, whereas there is no reduction due to sufficiency under the proportional odds model. In spite of these attractive features, the model has been applied less, as there are issues with maximum likelihood estimation and likelihood based testing approaches due to non-linearity and lack of identifiability of the parameters. We present comprehensive Bayesian inference and model comparison procedure for this class of models as an alternative to the classical frequentist approach. We illustrate our methodology by analyzing data from The Flint Men’s Health Study, a case-control study of prostate cancer in African-American men aged 40 to 79 years. We use clinical staging of prostate cancer in terms of Tumors, Nodes and Metastatsis (TNM) as the categorical response of interest. PMID:19731262

Gratitude depends on the relational model of communal sharing.

PubMed

Simão, Cláudia; Seibt, Beate

2014-01-01

We studied the relation between benefits, perception of social relationships and gratitude. Across three studies, we provide evidence that benefits increase gratitude to the extent to which one applies a mental model of a communal relationship. In Study 1, the communal sharing relational model, and no other relational models, predicted the amount of gratitude participants felt after imagining receiving a benefit from a new acquaintance. In Study 2, participants recalled a large benefit they had received. Applying a communal sharing relational model increased feelings of gratitude for the benefit. In Study 3, we manipulated whether the participant or another person received a benefit from an unknown other. Again, we found that the extent of communal sharing perceived in the relationship with the stranger predicted gratitude. An additional finding of Study 2 was that communal sharing predicted future gratitude regarding the relational partner in a longitudinal design. To conclude, applying a communal sharing model predicts gratitude regarding concrete benefits and regarding the relational partner, presumably because one perceives the communal partner as motivated to meet one's needs. Finally, in Study 3, we found in addition that being the recipient of a benefit without opportunity to repay directly increased communal sharing, and indirectly increased gratitude. These circumstances thus seem to favor the attribution of communal norms, leading to a communal sharing representation and in turn to gratitude. We discuss the importance of relational models as mental representations of relationships for feelings of gratitude.

Gratitude Depends on the Relational Model of Communal Sharing

PubMed Central

Simão, Cláudia; Seibt, Beate

2014-01-01

We studied the relation between benefits, perception of social relationships and gratitude. Across three studies, we provide evidence that benefits increase gratitude to the extent to which one applies a mental model of a communal relationship. In Study 1, the communal sharing relational model, and no other relational models, predicted the amount of gratitude participants felt after imagining receiving a benefit from a new acquaintance. In Study 2, participants recalled a large benefit they had received. Applying a communal sharing relational model increased feelings of gratitude for the benefit. In Study 3, we manipulated whether the participant or another person received a benefit from an unknown other. Again, we found that the extent of communal sharing perceived in the relationship with the stranger predicted gratitude. An additional finding of Study 2 was that communal sharing predicted future gratitude regarding the relational partner in a longitudinal design. To conclude, applying a communal sharing model predicts gratitude regarding concrete benefits and regarding the relational partner, presumably because one perceives the communal partner as motivated to meet one's needs. Finally, in Study 3, we found in addition that being the recipient of a benefit without opportunity to repay directly increased communal sharing, and indirectly increased gratitude. These circumstances thus seem to favor the attribution of communal norms, leading to a communal sharing representation and in turn to gratitude. We discuss the importance of relational models as mental representations of relationships for feelings of gratitude. PMID:24465933

A Laparoscopic Swine Model of Noncompressible Torso Hemorrhage

DTIC Science & Technology

2014-01-01

Various porcine models of hemorrhage have been developed for civilian and military trauma research. However, the predominant contemporary models lack...significant predictors of mortality. CONCLUSION: This study describes a model of NCTH that reflects clinically relevant physiology in trauma and...uncontrolled hemorrhage. In addition, it quantitatively assesses the role of the swine contractile spleen in the described model. (J Trauma Acute Care Surg

Identifying Students' Mental Models of Sound Propagation: The Role of Conceptual Blending in Understanding Conceptual Change

ERIC Educational Resources Information Center

Hrepic, Zdeslav; Zollman, Dean A.; Rebello, N. Sanjay

2010-01-01

We investigated introductory physics students' mental models of sound propagation. We used a phenomenographic method to analyze the data in the study. In addition to the scientifically accepted Wave model, students used the "Entity" model to describe the propagation of sound. In this latter model sound is a self-standing entity,…

Modeling and Diagnostic Software for Liquefying-Fuel Rockets

NASA Technical Reports Server (NTRS)

Poll, Scott; Iverson, David; Ou, Jeremy; Sanderfer, Dwight; Patterson-Hine, Ann

2005-01-01

A report presents a study of five modeling and diagnostic computer programs considered for use in an integrated vehicle health management (IVHM) system during testing of liquefying-fuel hybrid rocket engines in the Hybrid Combustion Facility (HCF) at NASA Ames Research Center. Three of the programs -- TEAMS, L2, and RODON -- are model-based reasoning (or diagnostic) programs. The other two programs -- ICS and IMS -- do not attempt to isolate the causes of failures but can be used for detecting faults. In the study, qualitative models (in TEAMS and L2) and quantitative models (in RODON) having varying scope and completeness were created. Each of the models captured the structure and behavior of the HCF as a physical system. It was noted that in the cases of the qualitative models, the temporal aspects of the behavior of the HCF and the abstraction of sensor data are handled outside of the models, and it is necessary to develop additional code for this purpose. A need for additional code was also noted in the case of the quantitative model, though the amount of development effort needed was found to be less than that for the qualitative models.

Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments

NASA Astrophysics Data System (ADS)

Huang, Pengnian; Li, Zhijia; Chen, Ji; Li, Qiaoling; Yao, Cheng

2016-11-01

To simulate the hydrological processes in semi-arid areas properly is still challenging. This study assesses the impact of different modeling strategies on simulating flood processes in semi-arid catchments. Four classic hydrological models, TOPMODEL, XINANJIANG (XAJ), SAC-SMA and TANK, were selected and applied to three semi-arid catchments in North China. Based on analysis and comparison of the simulation results of these classic models, four new flexible models were constructed and used to further investigate the suitability of various modeling strategies for semi-arid environments. Numerical experiments were also designed to examine the performances of the models. The results show that in semi-arid catchments a suitable model needs to include at least one nonlinear component to simulate the main process of surface runoff generation. If there are more than two nonlinear components in the hydrological model, they should be arranged in parallel, rather than in series. In addition, the results show that the parallel nonlinear components should be combined by multiplication rather than addition. Moreover, this study reveals that the key hydrological process over semi-arid catchments is the infiltration excess surface runoff, a non-linear component.

Regression mixture models: Does modeling the covariance between independent variables and latent classes improve the results?

PubMed Central

Lamont, Andrea E.; Vermunt, Jeroen K.; Van Horn, M. Lee

2016-01-01

Regression mixture models are increasingly used as an exploratory approach to identify heterogeneity in the effects of a predictor on an outcome. In this simulation study, we test the effects of violating an implicit assumption often made in these models – i.e., independent variables in the model are not directly related to latent classes. Results indicated that the major risk of failing to model the relationship between predictor and latent class was an increase in the probability of selecting additional latent classes and biased class proportions. Additionally, this study tests whether regression mixture models can detect a piecewise relationship between a predictor and outcome. Results suggest that these models are able to detect piecewise relations, but only when the relationship between the latent class and the predictor is included in model estimation. We illustrate the implications of making this assumption through a re-analysis of applied data examining heterogeneity in the effects of family resources on academic achievement. We compare previous results (which assumed no relation between independent variables and latent class) to the model where this assumption is lifted. Implications and analytic suggestions for conducting regression mixture based on these findings are noted. PMID:26881956

Testing the effectiveness of family therapeutic assessment: a case study using a time-series design.

PubMed

Smith, Justin D; Wolf, Nicole J; Handler, Leonard; Nash, Michael R

2009-11-01

We describe a family Therapeutic Assessment (TA) case study employing 2 assessors, 2 assessment rooms, and a video link. In the study, we employed a daily measures time-series design with a pretreatment baseline and follow-up period to examine the family TA treatment model. In addition to being an illustrative addition to a number of clinical reports suggesting the efficacy of family TA, this study is the first to apply a case-based time-series design to test whether family TA leads to clinical improvement and also illustrates when that improvement occurs. Results support the trajectory of change proposed by Finn (2007), the TA model's creator, who posits that benefits continue beyond the formal treatment itself.

Genetic and environmental contributions to body mass index: comparative analysis of monozygotic twins, dizygotic twins and same-age unrelated siblings.

PubMed

Segal, N L; Feng, R; McGuire, S A; Allison, D B; Miller, S

2009-01-01

Earlier studies have established that a substantial percentage of variance in obesity-related phenotypes is explained by genetic components. However, only one study has used both virtual twins (VTs) and biological twins and was able to simultaneously estimate additive genetic, non-additive genetic, shared environmental and unshared environmental components in body mass index (BMI). Our current goal was to re-estimate four components of variance in BMI, applying a more rigorous model to biological and virtual multiples with additional data. Virtual multiples share the same family environment, offering unique opportunities to estimate common environmental influence on phenotypes that cannot be separated from the non-additive genetic component using only biological multiples. Data included 929 individuals from 164 monozygotic twin pairs, 156 dizygotic twin pairs, five triplet sets, one quadruplet set, 128 VT pairs, two virtual triplet sets and two virtual quadruplet sets. Virtual multiples consist of one biological child (or twins or triplets) plus one same-aged adoptee who are all raised together since infancy. We estimated the additive genetic, non-additive genetic, shared environmental and unshared random components in BMI using a linear mixed model. The analysis was adjusted for age, age(2), age(3), height, height(2), height(3), gender and race. Both non-additive genetic and common environmental contributions were significant in our model (P-values<0.0001). No significant additive genetic contribution was found. In all, 63.6% (95% confidence interval (CI) 51.8-75.3%) of the total variance of BMI was explained by a non-additive genetic component, 25.7% (95% CI 13.8-37.5%) by a common environmental component and the remaining 10.7% by an unshared component. Our results suggest that genetic components play an essential role in BMI and that common environmental factors such as diet or exercise also affect BMI. This conclusion is consistent with our earlier study using a smaller sample and shows the utility of virtual multiples for separating non-additive genetic variance from common environmental variance.

Operative simulation of anterior clinoidectomy using a rapid prototyping model molded by a three-dimensional printer.

PubMed

Okonogi, Shinichi; Kondo, Kosuke; Harada, Naoyuki; Masuda, Hiroyuki; Nemoto, Masaaki; Sugo, Nobuo

2017-09-01

As the anatomical three-dimensional (3D) positional relationship around the anterior clinoid process (ACP) is complex, experience of many surgeries is necessary to understand anterior clinoidectomy (AC). We prepared a 3D synthetic image from computed tomographic angiography (CTA) and magnetic resonance imaging (MRI) data and a rapid prototyping (RP) model from the imaging data using a 3D printer. The objective of this study was to evaluate anatomical reproduction of the 3D synthetic image and intraosseous region after AC in the RP model. In addition, the usefulness of the RP model for operative simulation was investigated. The subjects were 51 patients who were examined by CTA and MRI before surgery. The size of the ACP, thickness and length of the optic nerve and artery, and intraosseous length after AC were measured in the 3D synthetic image and RP model, and reproducibility in the RP model was evaluated. In addition, 10 neurosurgeons performed AC in the completed RP models to investigate their usefulness for operative simulation. The RP model reproduced the region in the vicinity of the ACP in the 3D synthetic image, including the intraosseous region, at a high accuracy. In addition, drilling of the RP model was a useful operative simulation method of AC. The RP model of the vicinity of ACP, prepared using a 3D printer, showed favorable anatomical reproducibility, including reproduction of the intraosseous region. In addition, it was concluded that this RP model is useful as a surgical education tool for drilling.

LOS selective fading and AN/FRC-170(V) radio hybrid computer simulation phase A report

NASA Astrophysics Data System (ADS)

Klukis, M. K.; Lyon, T. I.; Walker, R.

1981-09-01

This report documents results of the first phase of modeling, simulation and study of the dual diversity AN/FRC-170(V) radio and frequency selective fading line of sight channel. Both hybrid computer and circuit technologies were used to develop a fast, accurate and flexible simulation tool to investigate changes and proposed improvements to the design of the AN/FRC-170(V) radio. In addition to the simulation study, a remote hybrid computer terminal was provided to DCEC for interactive study of the modeled radio and channel. Simulated performance of the radio for Rayleigh, line of sight two ray channels, and additive noise are included in the report.

Electron electric dipole moment in mirror fermion model with electroweak scale non-sterile right-handed neutrinos

NASA Astrophysics Data System (ADS)

Chang, Chia-Feng; Hung, P. Q.; Nugroho, Chrisna Setyo; Tran, Van Que; Yuan, Tzu-Chiang

2018-03-01

The electric dipole moment of the electron is studied in detail in an extended mirror fermion model with the following unique features of (a) right-handed neutrinos are non-sterile and have masses at the electroweak scale, and (b) a horizontal symmetry of the tetrahedral group is used in the lepton and scalar sectors. We study the constraint on the parameter space of the model imposed by the latest ACME experimental limit on electron electric dipole moment. Other low energy experimental observables such as the anomalous magnetic dipole moment of the muon, charged lepton flavor violating processes like muon decays into electron plus photon and muon-to-electron conversion in titanium, gold and lead are also considered in our analysis for comparison. In addition to the well-known CP violating Dirac and Majorana phases in the neutrino mixing matrix, the dependence of additional phases of the new Yukawa couplings in the model is studied in detail for all these low energy observables.

Influence of Alveolar Bone Defects on the Stress Distribution in Quad Zygomatic Implant-Supported Maxillary Prosthesis.

PubMed

Duan, Yuanyuan; Chandran, Ravi; Cherry, Denise

The purpose of this study was to create three-dimensional composite models of quad zygomatic implant-supported maxillary prostheses with a variety of alveolar bone defects around implant sites, and to investigate the stress distribution in the surrounding bone using the finite element analysis (FEA) method. Three-dimensional models of titanium zygomatic implants, maxillary prostheses, and human skulls were created and assembled using Mimics based on microcomputed tomography and cone beam computed tomography images. A variety of additional bone defects were created at the locations of four zygomatic implants to simulate multiple clinical scenarios. The volume meshes were created and exported into FEA software. Material properties were assigned respectively for all the structures, and von Mises stress data were collected and plotted in the postprocessing module. The maximum stress in the surrounding bone was located in the crestal bone around zygomatic implants. The maximum stress in the prostheses was located at the angled area of the implant-abutment connection. The model with anterior defects had a higher peak stress value than the model with posterior defects. All the models with additional bone defects had higher maximum stress values than the control model without additional bone loss. Additional alveolar bone loss has a negative influence on the stress concentration in the surrounding bone of quad zygomatic implant-supported prostheses. More care should be taken if these additional bone defects are at the sites of anterior zygomatic implants.

Assessing the Impact of Drug Use on Hospital Costs

PubMed Central

Stuart, Bruce C; Doshi, Jalpa A; Terza, Joseph V

2009-01-01

Objective To assess whether outpatient prescription drug utilization produces offsets in the cost of hospitalization for Medicare beneficiaries. Data Sources/Study Setting The study analyzed a sample (N=3,101) of community-dwelling fee-for-service U.S. Medicare beneficiaries drawn from the 1999 and 2000 Medicare Current Beneficiary Surveys. Study Design Using a two-part model specification, we regressed any hospital admission (part 1: probit) and hospital spending by those with one or more admissions (part 2: nonlinear least squares regression) on drug use in a standard model with strong covariate controls and a residual inclusion instrumental variable (IV) model using an exogenous measure of drug coverage as the instrument. Principal Findings The covariate control model predicted that each additional prescription drug used (mean=30) raised hospital spending by $16 (p<.001). The residual inclusion IV model prediction was that each additional prescription fill reduced hospital spending by $104 (p<.001). Conclusions The findings indicate that drug use is associated with cost offsets in hospitalization among Medicare beneficiaries, once omitted variable bias is corrected using an IV technique appropriate for nonlinear applications. PMID:18783453

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality.

PubMed

Yang, Lei; Qin, Guoyou; Zhao, Naiqing; Wang, Chunfang; Song, Guixiang

2012-10-30

Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton's method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality

PubMed Central

2012-01-01

Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Methods Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton’s method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. Results In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. Conclusions GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies. PMID:23110601

Metal mixture modeling evaluation project: 2. Comparison of four modeling approaches.

PubMed

Farley, Kevin J; Meyer, Joseph S; Balistrieri, Laurie S; De Schamphelaere, Karel A C; Iwasaki, Yuichi; Janssen, Colin R; Kamo, Masashi; Lofts, Stephen; Mebane, Christopher A; Naito, Wataru; Ryan, Adam C; Santore, Robert C; Tipping, Edward

2015-04-01

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the US Geological Survey (USA), HDR|HydroQual (USA), and the Centre for Ecology and Hydrology (United Kingdom) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME workshop in Brussels, Belgium (May 2012), is provided in the present study. Overall, the models were found to be similar in structure (free ion activities computed by the Windermere humic aqueous model [WHAM]; specific or nonspecific binding of metals/cations in or on the organism; specification of metal potency factors or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single vs multiple types of binding sites on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong interrelationships among the model parameters (binding constants, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed. © 2014 SETAC.

Probability of Detection (POD) as a statistical model for the validation of qualitative methods.

PubMed

Wehling, Paul; LaBudde, Robert A; Brunelle, Sharon L; Nelson, Maria T

2011-01-01

A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.

Animal models for studying female genital tract infection with Chlamydia trachomatis.

PubMed

De Clercq, Evelien; Kalmar, Isabelle; Vanrompay, Daisy

2013-09-01

Chlamydia trachomatis is a Gram-negative obligate intracellular bacterial pathogen. It is the leading cause of bacterial sexually transmitted disease in the world, with more than 100 million new cases of genital tract infections with C. trachomatis occurring each year. Animal models are indispensable for the study of C. trachomatis infections and the development and evaluation of candidate vaccines. In this paper, the most commonly used animal models to study female genital tract infections with C. trachomatis will be reviewed, namely, the mouse, guinea pig, and nonhuman primate models. Additionally, we will focus on the more recently developed pig model.

Additive-induced aggregate changes of two structurally similar dyes in aqueous solutions: A comparative photophysical study.

PubMed

Ghanadzadeh Gilani, A; Poormohammadi-Ahandani, Z; Kian, R

2018-01-15

Absorption and emission spectral characteristics of the two structurally similar phenothiazine dyes, azure B and toluidine blue, in aqueous solutions of the two sets of molecular additives (ureas and monosaccharides) were studied as a function of the dye and additive concentrations. The absorption spectra of the dyes were also studied in pure tetramethylurea with an aprotic nature. The spectral data were analyzed using DECOM Program. The dimer structure of the interacting molecules in these dyes was discussed using the exciton model. The urea class of additives was found to act as water structure-breakers over the range of studied concentration. The carbohydrate additives were found to act as water structure-breakers at low concentrations. However, the water structure breaking process may be disfavored by the additive-additive interactions at higher concentrations. It can be concluded that at low additive concentrations, the main driving force for breaking the dye association is water-additive interaction, which disrupts the water hydrogen bonds induced by the additives. However, at the high additive concentrations, the different phenomena including additive-additive and additive-dye interactions can change the structure, strength, and aggregative properties of the dyes. Finally, the urea in water induces noticeably fluorescence quenching in emission spectra of both the dyes. Copyright © 2017 Elsevier B.V. All rights reserved.

Additive-induced aggregate changes of two structurally similar dyes in aqueous solutions: A comparative photophysical study

NASA Astrophysics Data System (ADS)

Ghanadzadeh Gilani, A.; Poormohammadi-Ahandani, Z.; Kian, R.

2018-01-01

Absorption and emission spectral characteristics of the two structurally similar phenothiazine dyes, azure B and toluidine blue, in aqueous solutions of the two sets of molecular additives (ureas and monosaccharides) were studied as a function of the dye and additive concentrations. The absorption spectra of the dyes were also studied in pure tetramethylurea with an aprotic nature. The spectral data were analyzed using DECOM Program. The dimer structure of the interacting molecules in these dyes was discussed using the exciton model. The urea class of additives was found to act as water structure-breakers over the range of studied concentration. The carbohydrate additives were found to act as water structure-breakers at low concentrations. However, the water structure breaking process may be disfavored by the additive-additive interactions at higher concentrations. It can be concluded that at low additive concentrations, the main driving force for breaking the dye association is water-additive interaction, which disrupts the water hydrogen bonds induced by the additives. However, at the high additive concentrations, the different phenomena including additive-additive and additive-dye interactions can change the structure, strength, and aggregative properties of the dyes. Finally, the urea in water induces noticeably fluorescence quenching in emission spectra of both the dyes.

Modelling Long Term Disability following Injury: Comparison of Three Approaches for Handling Multiple Injuries

PubMed Central

Gabbe, Belinda J.; Harrison, James E.; Lyons, Ronan A.; Jolley, Damien

2011-01-01

Background Injury is a leading cause of the global burden of disease (GBD). Estimates of non-fatal injury burden have been limited by a paucity of empirical outcomes data. This study aimed to (i) establish the 12-month disability associated with each GBD 2010 injury health state, and (ii) compare approaches to modelling the impact of multiple injury health states on disability as measured by the Glasgow Outcome Scale – Extended (GOS-E). Methods 12-month functional outcomes for 11,337 survivors to hospital discharge were drawn from the Victorian State Trauma Registry and the Victorian Orthopaedic Trauma Outcomes Registry. ICD-10 diagnosis codes were mapped to the GBD 2010 injury health states. Cases with a GOS-E score >6 were defined as “recovered.” A split dataset approach was used. Cases were randomly assigned to development or test datasets. Probability of recovery for each health state was calculated using the development dataset. Three logistic regression models were evaluated: a) additive, multivariable; b) “worst injury;” and c) multiplicative. Models were adjusted for age and comorbidity and investigated for discrimination and calibration. Findings A single injury health state was recorded for 46% of cases (1–16 health states per case). The additive (C-statistic 0.70, 95% CI: 0.69, 0.71) and “worst injury” (C-statistic 0.70; 95% CI: 0.68, 0.71) models demonstrated higher discrimination than the multiplicative (C-statistic 0.68; 95% CI: 0.67, 0.70) model. The additive and “worst injury” models demonstrated acceptable calibration. Conclusions The majority of patients survived with persisting disability at 12-months, highlighting the importance of improving estimates of non-fatal injury burden. Additive and “worst” injury models performed similarly. GBD 2010 injury states were moderately predictive of recovery 1-year post-injury. Further evaluation using additional measures of health status and functioning and comparison with the GBD 2010 disability weights will be needed to optimise injury states for future GBD studies. PMID:21984951

Examining the Utility of Topic Models for Linguistic Analysis of Couple Therapy

ERIC Educational Resources Information Center

Doeden, Michelle A.

2012-01-01

This study examined the basic utility of topic models, a computational linguistics model for text-based data, to the investigation of the process of couple therapy. Linguistic analysis offers an additional lens through which to examine clinical data, and the topic model is presented as a novel methodology within couple and family psychology that…

The Effects of Autocorrelation on the Curve-of-Factors Growth Model

ERIC Educational Resources Information Center

Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.

2011-01-01

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

Simultaneous statistical bias correction of multiplePM2.5 species from a regional photochemical grid model

EPA Science Inventory

In recent years environmental epidemiologists have begun utilizing regionalscale air quality computer models to predict ambient air pollution concentrations in health studies instead of or in addition to monitoring data from central sites. The advantages of using such models i...

Lake Michigan lake trout PCB model forecast post audit (oral presentation)

EPA Science Inventory

Scenario forecasts for total PCBs in Lake Michigan (LM) lake trout were conducted using the linked LM2-Toxics and LM Food Chain models, supported by a suite of additional LM models. Efforts were conducted under the Lake Michigan Mass Balance Study and the post audit represents an...

Lake Michigan lake trout PCB model forecast post audit

EPA Science Inventory

Scenario forecasts for total PCBs in Lake Michigan (LM) lake trout were conducted using the linked LM2-Toxics and LM Food Chain models, supported by a suite of additional LM models. Efforts were conducted under the Lake Michigan Mass Balance Study and the post audit represents th...

Freight data architecture business process, logical data model, and physical data model.

DOT National Transportation Integrated Search

2014-09-01

This document summarizes the study teams efforts to establish data-sharing partnerships : and relay the lessons learned. In addition, it provides information on a prototype freight data : architecture and supporting description and specifications ...

The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Samaniego, Luis; Mai, Juliane; Kumar, Rohini; Thober, Stephan; Zink, Matthias; Schäfer, David; Savenije, Hubert H. G.; Hrachowitz, Markus

2016-03-01

Heterogeneity of landscape features like terrain, soil, and vegetation properties affects the partitioning of water and energy. However, it remains unclear to what extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated into the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge-based model constraints reduces model uncertainty, and whether (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge-based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as an overall measure of model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 %, respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. In addition, it was shown that suitable semi-quantitative prior constraints in combination with the transfer-function-based regularization approach of mHM can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

Modeling per capita state health expenditure variation: state-level characteristics matter.

PubMed

Cuckler, Gigi; Sisko, Andrea

2013-01-01

In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991-2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation.

FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model.

PubMed

Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

2014-01-01

A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well.

Modeling Per Capita State Health Expenditure Variation: State-Level Characteristics Matter

PubMed Central

Cuckler, Gigi; Sisko, Andrea

2013-01-01

Objective In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. Data Source We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991–2009, produced by the Centers for Medicare & Medicaid Services’ Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. Principal Findings State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation. PMID:24834363

Impact of species delimitation and sampling on niche models and phylogeographical inference: A case study of the East African reed frog Hyperolius substriatus Ahl, 1931.

PubMed

Bittencourt-Silva, Gabriela B; Lawson, Lucinda P; Tolley, Krystal A; Portik, Daniel M; Barratt, Christopher D; Nagel, Peter; Loader, Simon P

2017-09-01

Ecological niche models (ENMs) have been used in a wide range of ecological and evolutionary studies. In biogeographic studies these models have, among other things, helped in the discovery of new allopatric populations, and even new species. However, small sample sizes and questionable taxonomic delimitation can challenge models, often decreasing their accuracy. Herein we examine the sensitivity of ENMs to the addition of new, geographically isolated populations, and the impact of applying different taxonomic delimitations. The East African reed frog Hyperolius substriatus Ahl, 1931 was selected as a case study because it has been the subject of previous ENM predictions. Our results suggest that addition of new data and reanalysis of species lineages of H. substriatus improved our understanding of the evolutionary history of this group of frogs. ENMs provided robust predictions, even when some populations were deliberately excluded from the models. Splitting the lineages based on genetic relationships and analysing the ENMs separately provided insights about the biogeographical processes that led to the current distribution of H. substriatus. Copyright © 2017 Elsevier Inc. All rights reserved.

Validation analysis of probabilistic models of dietary exposure to food additives.

PubMed

Gilsenan, M B; Thompson, R L; Lambe, J; Gibney, M J

2003-10-01

The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.

Functional Resilience and Response to a Dietary Additive (Kefir) in Models of Foregut and Hindgut Microbial Fermentation In Vitro

PubMed Central

de la Fuente, Gabriel; Jones, Eleanor; Jones, Shann; Newbold, Charles J.

2017-01-01

Stability in gut ecosystems is an important area of study that impacts on the use of additives and is related with several pathologies. Kefir is a fermented milk drink made with a consortium of yeast and bacteria as a fermentation starter, of which the use as additive in companion and livestock animals has increased in the last few years. To investigate the effect of kefir milk on foregut and hindgut digestive systems, an in vitro approach was followed. Either rumen fluid or horse fecal contents were used as a microbial inoculate and the inclusion of kefir (fresh, autoclaved, or pasteurized) was tested. Gas production over 72 h of incubation was recorded and pH, volatile fatty acids (VFAs), lactate and ammonia concentration as well as lactic acid (LAB) and acetic acid bacteria, and yeast total numbers were also measured. Both direct and indirect (by subtracting their respective blanks) effects were analyzed and a multivariate analysis was performed to compare foregut and hindgut fermentation models. Addition of kefir boosted the fermentation by increasing molar concentration of VFAs and ammonia and shifting the Acetate to Propionate ratio in both models but heat processing techniques like pasteurization or autoclaving influenced the way the kefir is fermented and reacts with the present microbiota. In terms of comparison between both models, the foregut model seems to be less affected by the inclusion of Kefir than the hindgut model. In terms of variability in the response, the hindgut model appeared to be more variable than the foregut model in the way that it reacted indirectly to the addition of different types of kefir. PMID:28702019

Functional Resilience and Response to a Dietary Additive (Kefir) in Models of Foregut and Hindgut Microbial Fermentation In Vitro.

PubMed

de la Fuente, Gabriel; Jones, Eleanor; Jones, Shann; Newbold, Charles J

2017-01-01

Stability in gut ecosystems is an important area of study that impacts on the use of additives and is related with several pathologies. Kefir is a fermented milk drink made with a consortium of yeast and bacteria as a fermentation starter, of which the use as additive in companion and livestock animals has increased in the last few years. To investigate the effect of kefir milk on foregut and hindgut digestive systems, an in vitro approach was followed. Either rumen fluid or horse fecal contents were used as a microbial inoculate and the inclusion of kefir (fresh, autoclaved, or pasteurized) was tested. Gas production over 72 h of incubation was recorded and pH, volatile fatty acids (VFAs), lactate and ammonia concentration as well as lactic acid (LAB) and acetic acid bacteria, and yeast total numbers were also measured. Both direct and indirect (by subtracting their respective blanks) effects were analyzed and a multivariate analysis was performed to compare foregut and hindgut fermentation models. Addition of kefir boosted the fermentation by increasing molar concentration of VFAs and ammonia and shifting the Acetate to Propionate ratio in both models but heat processing techniques like pasteurization or autoclaving influenced the way the kefir is fermented and reacts with the present microbiota. In terms of comparison between both models, the foregut model seems to be less affected by the inclusion of Kefir than the hindgut model. In terms of variability in the response, the hindgut model appeared to be more variable than the foregut model in the way that it reacted indirectly to the addition of different types of kefir.

Quality Professional Development for Secondary Science Teachers

ERIC Educational Resources Information Center

Mchazlett, Dwight Henry, Jr.

2015-01-01

This record of study (ROS) explores the perceptions of three high school biology teachers who implemented a form of the Japanese originated Lesson Study Professional Development (LS PD) model. Additionally, this ROS reports on the perceptions of the internal stakeholders with regard to the model's viability as a potential solution to a proposed…

3-D and quasi-2-D discrete element modeling of grain commingling in a bucket elevator boot system

USDA-ARS?s Scientific Manuscript database

Unwanted grain commingling impedes new quality-based grain handling systems and has proven to be an expensive and time consuming issue to study experimentally. Experimentally validated models may reduce the time and expense of studying grain commingling while providing additional insight into detail...

Accelerated cure of phenol-formaldehyde resins : studies with model compounds

Treesearch

Anthony H. Conner; Linda F. Lorenz; Kolby C. Hirth

2002-01-01

2-Hydroxymethylphenol (2-HMP) and 4-hydroxymethylphenol (4-HMP) were used as model compounds to study the reactions that occur during cure of phenol-formaldehyde (PF) resin to which cure accelerators (ethyl formate, propylene carbonate, g-butyrolactone, and triacetin) have been added. The addition of cure accelerators significantly increased the rate of condensation...

Enological Tannin Effect on Red Wine Color and Pigment Composition and Relevance of the Yeast Fermentation Products.

PubMed

García-Estévez, Ignacio; Alcalde-Eon, Cristina; Puente, Víctor; Escribano-Bailón, M Teresa

2017-11-23

Enological tannins are widely used in the winemaking process either to improve different wine characteristics (color stability, among others) or to compensate for low tannin levels. In this work, the influence of the addition of two different enological tannins, mainly composed of hydrolysable (ellagitannins) and condensed tannins, on the evolution of color and pigment composition of two different types of model systems containing the five main grape anthocyanins was studied. In addition, the effect of the addition of an enological tannin on the color and pigment composition of red wines made from Vitis vinifera L. cv Tempranillo grapes was also studied by high-performance liquid chromatography with diode array detection coupled to mass spectrometry (HPLC-DAD-MS). Results showed that, in model systems, the addition of the enological tannin favored the formation of anthocyanin-derived pigments, such as A-type and B-type vitisins and flavanol-anthocyanin condensation products, provided that the yeast precursors were previously supplied. Moreover, model systems containing the enological tannins were darker and showed higher values of chroma at the end of the study than control ones. The higher formation of these anthocyanin-derived pigments was also observed in the red wines containing the enological tannin. Moreover, these wine also showed lower lightness (L*) values and higher chroma (C* ab ) values than control wines, indicating a higher stabilization of color.

Linking Meteorology, Air Quality Models and Observations to ...

EPA Pesticide Factsheets

Epidemiologic studies are critical in establishing the association between exposure to air pollutants and adverse health effects. Results of epidemiologic studies are used by U.S. EPA in developing air quality standards to protect the public from the health effects of air pollutants. A major challenge in environmental epidemiology is adequate exposure characterization. Numerous health studies have used measurements from a few central-site ambient monitors to characterize air pollution exposures. Relying solely on central-site ambient monitors does not account for the spatial-heterogeneity of ambient air pollution patterns, the temporal variability in ambient concentrations, nor the influence of infiltration and indoor sources. Central-site monitoring becomes even more problematic for certain air pollutants that exhibit significant spatial heterogeneity. Statistical interpolation techniques and passive monitoring methods can provide additional spatial resolution in ambient concentration estimates. In addition, spatio-temporal models, which integrate GIS data and other factors, such as meteorology, have also been developed to produce more resolved estimates of ambient concentrations. Models, such as the Community Multi-Scale Air Quality (CMAQ) model, estimate ambient concentrations by combining information on meteorology, source emissions, and chemical-fate and transport. Hybrid modeling approaches, which integrate regional scale models with local scale dispersion

Mathematical and computational approaches can complement experimental studies of host-pathogen interactions.

PubMed

Kirschner, Denise E; Linderman, Jennifer J

2009-04-01

In addition to traditional and novel experimental approaches to study host-pathogen interactions, mathematical and computer modelling have recently been applied to address open questions in this area. These modelling tools not only offer an additional avenue for exploring disease dynamics at multiple biological scales, but also complement and extend knowledge gained via experimental tools. In this review, we outline four examples where modelling has complemented current experimental techniques in a way that can or has already pushed our knowledge of host-pathogen dynamics forward. Two of the modelling approaches presented go hand in hand with articles in this issue exploring fluorescence resonance energy transfer and two-photon intravital microscopy. Two others explore virtual or 'in silico' deletion and depletion as well as a new method to understand and guide studies in genetic epidemiology. In each of these examples, the complementary nature of modelling and experiment is discussed. We further note that multi-scale modelling may allow us to integrate information across length (molecular, cellular, tissue, organism, population) and time (e.g. seconds to lifetimes). In sum, when combined, these compatible approaches offer new opportunities for understanding host-pathogen interactions.

Studying the Warm Layer and the Hardening Factor in Cygnus X-1

NASA Technical Reports Server (NTRS)

Yao, Yangsen; Zhang, Shuangnan; Zhang, Xiaoling; Feng, Yuxin

2002-01-01

As the first dynamically determined black hole X-ray binary system, Cygnus X-1 has been studied extensively. However, its broadband spectrum observed with BeppoSax is still not well understood. Besides the soft excess described by the multi-color disk model (MCD), the power-law hard component and a broad excess feature above 10 keV (a disk reflection component), there is also an additional soft component around 1 keV, whose origin is not known currently. Here we propose that the additional soft component is due to the thermal Comptonization between the soft disk photons and a warm plasma cloud just above the disk, i.e., a warm layer. We use the Monte-Carlo technique to simulate this Compton scattering process and build a table model based on our simulation results. With this table model, we study the disk structure and estimate the hardening factor to the MCD component in Cygnus X-1.

The Shigella human challenge model.

PubMed

Porter, C K; Thura, N; Ranallo, R T; Riddle, M S

2013-02-01

Shigella is an important bacterial cause of infectious diarrhoea globally. The Shigella human challenge model has been used since 1946 for a variety of objectives including understanding disease pathogenesis, human immune responses and allowing for an early assessment of vaccine efficacy. A systematic review of the literature regarding experimental shigellosis in human subjects was conducted. Summative estimates were calculated by strain and dose. While a total of 19 studies evaluating nine strains at doses ranging from 10 to 1 × 1010 colony-forming units were identified, most studies utilized the S. sonnei strain 53G and the S. flexneri strain 2457T. Inoculum solution and pre-inoculation buffering has varied over time although diarrhoea attack rates do not appear to increase above 75-80%, and dysentery rates remain fairly constant, highlighting the need for additional dose-ranging studies. Expansion of the model to include additional strains from different serotypes will elucidate serotype and strain-specific outcome variability.

A flower-like Ising model. Thermodynamic properties

NASA Astrophysics Data System (ADS)

Mejdani, R.; Ifti, M.

1995-03-01

We consider a flower-like Ising model, in which there are some additional bonds (in the “flower-core”) compared to a pure Ising chain. To understand the behaviour of this system and particularly the competition between ferromagnetic (usual) bonds along the chain and antiferromagnetic (additional) bonds across the chain, we study analytically and iteratively the main thermodynamic quantities. Very interesting is, in the zero-field and zero-temperature limit, the behaviour of the magnetization and the susceptibility, closely related to the ground state configurations and their degeneracies. This degeneracy explains the existence of non-zero entropy at zero temperature, in our results. Also, this model could be useful for the experimental investigations in studying the saturation curves for the enzyme kinetics or the melting curves for DNA-denaturation in some flower-like configurations.

Mixed-effects models for estimating stand volume by means of small footprint airborne laser scanner data.

Treesearch

J. Breidenbach; E. Kublin; R. McGaughey; H.-E. Andersen; S. Reutebuch

2008-01-01

For this study, hierarchical data sets--in that several sample plots are located within a stand--were analyzed for study sites in the USA and Germany. The German data had an additional hierarchy as the stands are located within four distinct public forests. Fixed-effects models and mixed-effects models with a random intercept on the stand level were fit to each data...

Upper and Lower Limb Muscle Architecture of a 104 Year-Old Cadaver

PubMed Central

Infantolino, Benjamin

2016-01-01

Muscle architecture is an important component to typical musculoskeletal models. Previous studies of human muscle architecture have focused on a single joint, two adjacent joints, or an entire limb. To date, no study has presented muscle architecture for the upper and lower limbs of a single cadaver. Additionally, muscle architectural parameters from elderly cadavers are lacking, making it difficult to accurately model elderly populations. Therefore, the purpose of this study was to present muscle architecture of the upper and lower limbs of a 104 year old female cadaver. The major muscles of the upper and lower limbs were removed and the musculotendon mass, tendon mass, musculotendon length, tendon length, pennation angle, optimal fascicle length, physiological cross-sectional area, and tendon cross-sectional area were determined for each muscle. Data from this complete cadaver are presented in table format. The data from this study can be used to construct a musculoskeletal model of a specific individual who was ambulatory, something which has not been possible to date. This should increase the accuracy of the model output as the model will be representing a specific individual, not a synthesis of measurements from multiple individuals. Additionally, an elderly individual can be modeled which will provide insight into muscle function as we age. PMID:28033339

Upper and Lower Limb Muscle Architecture of a 104 Year-Old Cadaver.

PubMed

Ruggiero, Marissa; Cless, Daniel; Infantolino, Benjamin

2016-01-01

Muscle architecture is an important component to typical musculoskeletal models. Previous studies of human muscle architecture have focused on a single joint, two adjacent joints, or an entire limb. To date, no study has presented muscle architecture for the upper and lower limbs of a single cadaver. Additionally, muscle architectural parameters from elderly cadavers are lacking, making it difficult to accurately model elderly populations. Therefore, the purpose of this study was to present muscle architecture of the upper and lower limbs of a 104 year old female cadaver. The major muscles of the upper and lower limbs were removed and the musculotendon mass, tendon mass, musculotendon length, tendon length, pennation angle, optimal fascicle length, physiological cross-sectional area, and tendon cross-sectional area were determined for each muscle. Data from this complete cadaver are presented in table format. The data from this study can be used to construct a musculoskeletal model of a specific individual who was ambulatory, something which has not been possible to date. This should increase the accuracy of the model output as the model will be representing a specific individual, not a synthesis of measurements from multiple individuals. Additionally, an elderly individual can be modeled which will provide insight into muscle function as we age.

A New Look at Genetic and Environmental Architecture on Lipids Using Non-Normal Structural Equation Modeling in Male Twins: The NHLBI Twin Study.

PubMed

Wu, Sheng-Hui; Ozaki, Koken; Reed, Terry; Krasnow, Ruth E; Dai, Jun

2017-07-01

This study examined genetic and environmental influences on the lipid concentrations of 1028 male twins using the novel univariate non-normal structural equation modeling (nnSEM) ADCE and ACE models. In the best fitting nnSEM ADCE model that was also better than the nnSEM ACE model, additive genetic factors (A) explained 4%, dominant genetic factors (D) explained 17%, and common (C) and unique (E) environmental factors explained 47% and 33% of the total variance of high-density lipoprotein cholesterol (HDL-C). The percentage of variation explained for other lipids was 0% (A), 30% (D), 34% (C) and 37% (E) for low-density lipoprotein cholesterol (LDL-C); 30, 0, 31 and 39% for total cholesterol; and 0, 31, 12 and 57% for triglycerides. It was concluded that additive and dominant genetic factors simultaneously affected HDL-C concentrations but not other lipids. Common and unique environmental factors influenced concentrations of all lipids.

Empirically Based Composite Fracture Prediction Model From the Global Longitudinal Study of Osteoporosis in Postmenopausal Women (GLOW)

PubMed Central

Compston, Juliet E.; Chapurlat, Roland D.; Pfeilschifter, Johannes; Cooper, Cyrus; Hosmer, David W.; Adachi, Jonathan D.; Anderson, Frederick A.; Díez-Pérez, Adolfo; Greenspan, Susan L.; Netelenbos, J. Coen; Nieves, Jeri W.; Rossini, Maurizio; Watts, Nelson B.; Hooven, Frederick H.; LaCroix, Andrea Z.; March, Lyn; Roux, Christian; Saag, Kenneth G.; Siris, Ethel S.; Silverman, Stuart; Gehlbach, Stephen H.

2014-01-01

Context: Several fracture prediction models that combine fractures at different sites into a composite outcome are in current use. However, to the extent individual fracture sites have differing risk factor profiles, model discrimination is impaired. Objective: The objective of the study was to improve model discrimination by developing a 5-year composite fracture prediction model for fracture sites that display similar risk profiles. Design: This was a prospective, observational cohort study. Setting: The study was conducted at primary care practices in 10 countries. Patients: Women aged 55 years or older participated in the study. Intervention: Self-administered questionnaires collected data on patient characteristics, fracture risk factors, and previous fractures. Main Outcome Measure: The main outcome is time to first clinical fracture of hip, pelvis, upper leg, clavicle, or spine, each of which exhibits a strong association with advanced age. Results: Of four composite fracture models considered, model discrimination (c index) is highest for an age-related fracture model (c index of 0.75, 47 066 women), and lowest for Fracture Risk Assessment Tool (FRAX) major fracture and a 10-site model (c indices of 0.67 and 0.65). The unadjusted increase in fracture risk for an additional 10 years of age ranges from 80% to 180% for the individual bones in the age-associated model. Five other fracture sites not considered for the age-associated model (upper arm/shoulder, rib, wrist, lower leg, and ankle) have age associations for an additional 10 years of age from a 10% decrease to a 60% increase. Conclusions: After examining results for 10 different bone fracture sites, advanced age appeared the single best possibility for uniting several different sites, resulting in an empirically based composite fracture risk model. PMID:24423345

Study the Seasonal Variability of Plankton and Forage Fish in the Gulf of Khambhat Using Npzfd Model

NASA Astrophysics Data System (ADS)

Kumar, V.; Kumar, S.

2016-02-01

Numerical modelling of marine ecology exploits several assumptions and it is indeed quite challenging to include marine ecological phenomena into a mathematical framework with too many unknown parameters. The governing ordinary differential equations represent the interaction of the biological and chemical processes in a marine environment. The key concern in the development of a numerical models are parameterizations based on output, viz., mathematical modelling of ecological system mainly depends on parameters and its variations. Almost, all constituents of each trophic level of marine food web are depended on phytoplankton, which are mostly influenced by initial slope of P-I curve and nutrient stock in the study domain. Whereas, the earlier plankton dynamic models rarely include a compartment of small fish and as an agent in zooplankton mortality, which is most important for the modelling of higher trophic level of marine species. A compartment of forage fish in the modelling of plankton dynamics has been given more realistic mortality rates of plankton, viz., they feed upon phytoplankton and zooplankton. The inclusion of an additional compartment increases complexity of earlier plankton dynamics model as it introduces additional unknown parameters, which has been specified for performing the numerical simulations.As a case study we applied our analysis to explain the aquatic ecology of Gulf of Khambhat (19o 48' N - 22o20' N, 65o E - 72o40' E), west coast of India, which has rich bio-diversity and a high productive area in the form of plankton and forage fish. It has elevated turbidity and varying geography location, viz., one of the regions among world's ocean with high biological productivity.The model presented in this study is able to bring out the essential features of the observed data; that includes the bimodal oscillations in the observed data, monthly mean chlorophyll-a in the SeaWiFs/MODIS Aqua data and in-situ data of plankton. The additional compartment of forage fish and detritus in NPZFD model represents a major structural difference from the earlier NPZ model.

Modeling the flux of metabolites in the juvenile hormone biosynthesis pathway using generalized additive models and ordinary differential equations.

PubMed

Martínez-Rincón, Raúl O; Rivera-Pérez, Crisalejandra; Diambra, Luis; Noriega, Fernando G

2017-01-01

Juvenile hormone (JH) regulates development and reproductive maturation in insects. The corpora allata (CA) from female adult mosquitoes synthesize fluctuating levels of JH, which have been linked to the ovarian development and are influenced by nutritional signals. The rate of JH biosynthesis is controlled by the rate of flux of isoprenoids in the pathway, which is the outcome of a complex interplay of changes in precursor pools and enzyme levels. A comprehensive study of the changes in enzymatic activities and precursor pool sizes have been previously reported for the mosquito Aedes aegypti JH biosynthesis pathway. In the present studies, we used two different quantitative approaches to describe and predict how changes in the individual metabolic reactions in the pathway affect JH synthesis. First, we constructed generalized additive models (GAMs) that described the association between changes in specific metabolite concentrations with changes in enzymatic activities and substrate concentrations. Changes in substrate concentrations explained 50% or more of the model deviances in 7 of the 13 metabolic steps analyzed. Addition of information on enzymatic activities almost always improved the fitness of GAMs built solely based on substrate concentrations. GAMs were validated using experimental data that were not included when the model was built. In addition, a system of ordinary differential equations (ODE) was developed to describe the instantaneous changes in metabolites as a function of the levels of enzymatic catalytic activities. The results demonstrated the ability of the models to predict changes in the flux of metabolites in the JH pathway, and can be used in the future to design and validate experimental manipulations of JH synthesis.

Effects of Rhenium Addition on the Temporal Evolution of the Nanostructure and Chemistry of a Model Ni-Cr-Al Superalloy. 2; Analysis of the Coarsening Behavior

NASA Technical Reports Server (NTRS)

Yoon, Kevin E.; Noebe, Ronald D.; Seidman, David N.

2007-01-01

The temporal evolution of the nanostructure and chemistry of a model Ni-8.5 at.% Cr-10 at.% Al alloy with the addition of 2 at.% Re was studied using transmission electron microscopy and atom-probe tomography in order to measure the number density and mean radius of the y' (LIZ) precipitates and the chemistry of the y'-precipitates and the y (fcc)-matrix. In this article, the coarsening behavior of the y'-precipitates is discussed in detail and compared with the Umantsev-Olson model for multi-component alloys. In addition, the experimental results are evaluated with PrecipiCalc(TradeMark) simulations. The results show that the diffusivities of the solute elements play a major role in the coarsening behavior of the y'-precipitates and that the addition of Re retards the coarsening kinetics and stabilizes the spheroidal morphology of the precipitates by reducing the interfacial energy.

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

Diagnostic utility of appetite loss in addition to existing prediction models for community-acquired pneumonia in the elderly: a prospective diagnostic study in acute care hospitals in Japan

PubMed Central

Yamamoto, Yosuke; Terada, Kazuhiko; Ohta, Mitsuyasu; Mikami, Wakako; Yokota, Hajime; Hayashi, Michio; Miyashita, Jun; Azuma, Teruhisa; Fukuma, Shingo; Fukuhara, Shunichi

2017-01-01

Objective Diagnosis of community-acquired pneumonia (CAP) in the elderly is often delayed because of atypical presentation and non-specific symptoms, such as appetite loss, falls and disturbance in consciousness. The aim of this study was to investigate the external validity of existing prediction models and the added value of the non-specific symptoms for the diagnosis of CAP in elderly patients. Design Prospective cohort study. Setting General medicine departments of three teaching hospitals in Japan. Participants A total of 109 elderly patients who consulted for upper respiratory symptoms between 1 October 2014 and 30 September 2016. Main outcome measures The reference standard for CAP was chest radiograph evaluated by two certified radiologists. The existing models were externally validated for diagnostic performance by calibration plot and discrimination. To evaluate the additional value of the non-specific symptoms to the existing prediction models, we developed an extended logistic regression model. Calibration, discrimination, category-free net reclassification improvement (NRI) and decision curve analysis (DCA) were investigated in the extended model. Results Among the existing models, the model by van Vugt demonstrated the best performance, with an area under the curve of 0.75(95% CI 0.63 to 0.88); calibration plot showed good fit despite a significant Hosmer-Lemeshow test (p=0.017). Among the non-specific symptoms, appetite loss had positive likelihood ratio of 3.2 (2.0–5.3), negative likelihood ratio of 0.4 (0.2–0.7) and OR of 7.7 (3.0–19.7). Addition of appetite loss to the model by van Vugt led to improved calibration at p=0.48, NRI of 0.53 (p=0.019) and higher net benefit by DCA. Conclusions Information on appetite loss improved the performance of an existing model for the diagnosis of CAP in the elderly. PMID:29122806

Towards Additive Manufacture of Functional, Spline-Based Morphometric Models of Healthy and Diseased Coronary Arteries: In Vitro Proof-of-Concept Using a Porcine Template.

PubMed

Jewkes, Rachel; Burton, Hanna E; Espino, Daniel M

2018-02-02

The aim of this study is to assess the additive manufacture of morphometric models of healthy and diseased coronary arteries. Using a dissected porcine coronary artery, a model was developed with the use of computer aided engineering, with splines used to design arteries in health and disease. The model was altered to demonstrate four cases of stenosis displaying varying severity, based on published morphometric data available. Both an Objet Eden 250 printer and a Solidscape 3Z Pro printer were used in this analysis. A wax printed model was set into a flexible thermoplastic and was valuable for experimental testing with helical flow patterns observed in healthy models, dominating the distal LAD (left anterior descending) and left circumflex arteries. Recirculation zones were detected in all models, but were visibly larger in the stenosed cases. Resin models provide useful analytical tools for understanding the spatial relationships of blood vessels, and could be applied to preoperative planning techniques, but were not suitable for physical testing. In conclusion, it is feasible to develop blood vessel models enabling experimental work; further, through additive manufacture of bio-compatible materials, there is the possibility of manufacturing customized replacement arteries.

Towards Additive Manufacture of Functional, Spline-Based Morphometric Models of Healthy and Diseased Coronary Arteries: In Vitro Proof-of-Concept Using a Porcine Template

PubMed Central

Jewkes, Rachel; Burton, Hanna E.; Espino, Daniel M.

2018-01-01

The aim of this study is to assess the additive manufacture of morphometric models of healthy and diseased coronary arteries. Using a dissected porcine coronary artery, a model was developed with the use of computer aided engineering, with splines used to design arteries in health and disease. The model was altered to demonstrate four cases of stenosis displaying varying severity, based on published morphometric data available. Both an Objet Eden 250 printer and a Solidscape 3Z Pro printer were used in this analysis. A wax printed model was set into a flexible thermoplastic and was valuable for experimental testing with helical flow patterns observed in healthy models, dominating the distal LAD (left anterior descending) and left circumflex arteries. Recirculation zones were detected in all models, but were visibly larger in the stenosed cases. Resin models provide useful analytical tools for understanding the spatial relationships of blood vessels, and could be applied to preoperative planning techniques, but were not suitable for physical testing. In conclusion, it is feasible to develop blood vessel models enabling experimental work; further, through additive manufacture of bio-compatible materials, there is the possibility of manufacturing customized replacement arteries. PMID:29393899

Computer-aided design of liposomal drugs: In silico prediction and experimental validation of drug candidates for liposomal remote loading.

PubMed

Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

2014-01-10

Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs' structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al., J. Control. Release 160 (2012) 147-157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-Nearest Neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used by us in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. © 2013.

Computer-aided design of liposomal drugs: in silico prediction and experimental validation of drug candidates for liposomal remote loading

PubMed Central

Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

2014-01-01

Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs’ structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al, Journal of Controlled Release, 160(2012) 14–157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-nearest neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. PMID:24184343

Students’ mental model on heat convection concept and its relation with students conception on heat and temperature

NASA Astrophysics Data System (ADS)

Amalia, R.; Sari, I. M.; Sinaga, P.

2017-02-01

This research depended by previous studies that only to find out the misconceptions of students without figuring out the mechanism of the misconceptions. The mechanism of misconceptions can be studied more deeply with mental models. The purpose of this study was to find students ‘mental models of heat convection and its relation with students conception on heat and temperature. The method used in this study is exploratory mixed method design that implemented in one of the high schools in Bandung. The results showed that 7 mental models of heat convection in Chiou’s study (2013), only first model (diffusion-based convention), third model (evenly distributed convection) and fifth model (warmness topped convection II) were found and model hybrid convection as a new mental model. In addition, no specific relationship between mental models and categories of students’ conceptions on heat and temperature.

Finite element simulation and experimental verification of ultrasonic non-destructive inspection of defects in additively manufactured materials

NASA Astrophysics Data System (ADS)

Taheri, H.; Koester, L.; Bigelow, T.; Bond, L. J.

2018-04-01

Industrial applications of additively manufactured components are increasing quickly. Adequate quality control of the parts is necessary in ensuring safety when using these materials. Base material properties, surface conditions, as well as location and size of defects are some of the main targets for nondestructive evaluation of additively manufactured parts, and the problem of adequate characterization is compounded given the challenges of complex part geometry. Numerical modeling can allow the interplay of the various factors to be studied, which can lead to improved measurement design. This paper presents a finite element simulation verified by experimental results of ultrasonic waves scattering from flat bottom holes (FBH) in additive manufacturing materials. A focused beam immersion ultrasound transducer was used for both the modeling and simulations in the additive manufactured samples. The samples were SS17 4 PH steel samples made by laser sintering in a powder bed.

An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data

NASA Astrophysics Data System (ADS)

Shao, Yang; Campbell, James B.; Taff, Gregory N.; Zheng, Baojuan

2015-06-01

The Midwestern United States is one of the world's most important corn-producing regions. Monitoring and forecasting of corn yields in this intensive agricultural region are important activities to support food security, commodity markets, bioenergy industries, and formation of national policies. This study aims to develop forecasting models that have the capability to provide mid-season prediction of county-level corn yields for the entire Midwestern United States. We used multi-temporal MODIS NDVI (normalized difference vegetation index) 16-day composite data as the primary input, with digital elevation model (DEM) and parameter-elevation relationships on independent slopes model (PRISM) climate data as additional inputs. The DEM and PRISM data, along with three types of cropland masks were tested and compared to evaluate their impacts on model predictive accuracy. Our results suggested that the use of general cropland masks (e.g., summer crop or cultivated crops) generated similar results compared with use of an annual corn-specific mask. Leave-one-year-out cross-validation resulted in an average R2 of 0.75 and RMSE value of 1.10 t/ha. Using a DEM as an additional model input slightly improved performance, while inclusion of PRISM climate data appeared not to be important for our regional corn-yield model. Furthermore, our model has potential for real-time/early prediction. Our corn yield esitmates are available as early as late July, which is an improvement upon previous corn-yield prediction models. In addition to annual corn yield forecasting, we examined model uncertainties through spatial and temporal analysis of the model's predictive error distribution. The magnitude of predictive error (by county) appears to be associated with the spatial patterns of corn fields in the study area.

Improving students’ mathematical critical thinking through rigorous teaching and learning model with informal argument

NASA Astrophysics Data System (ADS)

Hamid, H.

2018-01-01

The purpose of this study is to analyze an improvement of students’ mathematical critical thinking (CT) ability in Real Analysis course by using Rigorous Teaching and Learning (RTL) model with informal argument. In addition, this research also attempted to understand students’ CT on their initial mathematical ability (IMA). This study was conducted at a private university in academic year 2015/2016. The study employed the quasi-experimental method with pretest-posttest control group design. The participants of the study were 83 students in which 43 students were in the experimental group and 40 students were in the control group. The finding of the study showed that students in experimental group outperformed students in control group on mathematical CT ability based on their IMA (high, medium, low) in learning Real Analysis. In addition, based on medium IMA the improvement of mathematical CT ability of students who were exposed to RTL model with informal argument was greater than that of students who were exposed to CI (conventional instruction). There was also no effect of interaction between RTL model and CI model with both (high, medium, and low) IMA increased mathematical CT ability. Finally, based on (high, medium, and low) IMA there was a significant improvement in the achievement of all indicators of mathematical CT ability of students who were exposed to RTL model with informal argument than that of students who were exposed to CI.

Constraints on holographic cosmologies from strong lensing systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cárdenas, Víctor H.; Bonilla, Alexander; Motta, Verónica

We use strongly gravitationally lensed (SGL) systems to put additional constraints on a set of holographic dark energy models. Data available in the literature (redshift and velocity dispersion) is used to obtain the Einstein radius and compare it with model predictions. We found that the ΛCDM is the best fit to the data. Although a preliminary statistical analysis seems to indicate that two of the holographic models studied show interesting agreement with observations, a stringent test lead us to the result that neither of the holographic models are competitive with the ΛCDM. These results highlight the importance of Strong Lensingmore » measurements to provide additional observational constraints to alternative cosmological models, which are necessary to shed some light into the dark universe.« less

A Preliminary Study of Perfectionism and Loneliness as Predictors of Depressive and Anxious Symptoms in Latinas: A Top-Down Test of a Model

ERIC Educational Resources Information Center

Chang, Edward C.; Hirsch, Jameson K.; Sanna, Lawrence J.; Jeglic, Elizabeth L.; Fabian, Cathryn G.

2011-01-01

In the present study, we used a top-down approach to examine perfectionism and loneliness as additive sociocognitive predictors of depressive and anxious symptoms in a sample of 121 Latina college students. Consistent with expectations, we found perfectionism and loneliness to be associated with both depressive and anxious symptoms. In addition,…

Modeling as an Anchoring Scientific Practice for Explaining Friction Phenomena

ERIC Educational Resources Information Center

Neilson, Drew; Campbell, Todd

2017-01-01

Through examining the day-to-day work of scientists, researchers in science studies have revealed how models are a central sense-making practice of scientists as they construct and critique explanations about how the universe works. Additionally, they allow predictions to be made using the tenets of the model. Given this, alongside research…

Identifying Multiple Levels of Discussion-Based Teaching Strategies for Constructing Scientific Models

ERIC Educational Resources Information Center

Williams, Grant; Clement, John

2015-01-01

This study sought to identify specific types of discussion-based strategies that two successful high school physics teachers using a model-based approach utilized in attempting to foster students' construction of explanatory models for scientific concepts. We found evidence that, in addition to previously documented dialogical strategies that…

Do Responses to Different Anthropogenic Forcings Add Linearly in Climate Models?

NASA Technical Reports Server (NTRS)

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; Bonfils, Celine; LeGrande, Allegra N.; Nazarenko, Larissa; Tsigaridis, Kostas

2015-01-01

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings; however, we demonstrate that there are significant nonlinearities in precipitation responses to di?erent forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to di?erences in ozone forcing arising from interactions between forcing agents. Our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.

Do responses to different anthropogenic forcings add linearly in climate models?

DOE PAGES

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; ...

2015-10-14

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM4) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings. However,more » we demonstrate that there are significant nonlinearities in precipitation responses to different forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to differences in ozone forcing arising from interactions between forcing agents. Lastly, our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.« less

Head flying characteristics in heat assisted magnetic recording considering various nanoscale heat transfer models

NASA Astrophysics Data System (ADS)

Hu, Yueqiang; Wu, Haoyu; Meng, Yonggang; Wang, Yu; Bogy, David

2018-01-01

The thermal issues in heat-assisted magnetic recording (HAMR) technology have drawn much attention in the recent literature. In this paper, the head flying characteristics and thermal performance of a HAMR system during the touch-down process considering different nanoscale heat transfer models across the head-disk interface are numerically studied. An optical-thermal-mechanical coupled model is first described. The coupling efficiency of the near field transducer is found to be dependent on the head disk clearance. The shortcomings of a constant disk-temperature model are investigated, which reveals the importance of considering the disk temperature as a variable. A study of the head flying on the disk is carried out using an air conduction model and additional near-field heat transfer models. It is shown that when the head disk interface is filled with a solid material caused by the laser-induced accumulation, the heat transfer coefficient can become unexpectedly large and the head's temperature can rise beyond desirable levels. Finally, the additional head protrusion due to the laser heating is investigated.

Impact of chemical proportions on the acute neurotoxicity of a mixture of seven carbamates in preweanling and adult rats.

PubMed

Moser, Virginia C; Padilla, Stephanie; Simmons, Jane Ellen; Haber, Lynne T; Hertzberg, Richard C

2012-09-01

Statistical design and environmental relevance are important aspects of studies of chemical mixtures, such as pesticides. We used a dose-additivity model to test experimentally the default assumptions of dose additivity for two mixtures of seven N-methylcarbamates (carbaryl, carbofuran, formetanate, methomyl, methiocarb, oxamyl, and propoxur). The best-fitting models were selected for the single-chemical dose-response data and used to develop a combined prediction model, which was then compared with the experimental mixture data. We evaluated behavioral (motor activity) and cholinesterase (ChE)-inhibitory (brain, red blood cells) outcomes at the time of peak acute effects following oral gavage in adult and preweanling (17 days old) Long-Evans male rats. The mixtures varied only in their mixing ratios. In the relative potency mixture, proportions of each carbamate were set at equitoxic component doses. A California environmental mixture was based on the 2005 sales of each carbamate in California. In adult rats, the relative potency mixture showed dose additivity for red blood cell ChE and motor activity, and brain ChE inhibition showed a modest greater-than additive (synergistic) response, but only at a middle dose. In rat pups, the relative potency mixture was either dose-additive (brain ChE inhibition, motor activity) or slightly less-than additive (red blood cell ChE inhibition). On the other hand, at both ages, the environmental mixture showed greater-than additive responses on all three endpoints, with significant deviations from predicted at most to all doses tested. Thus, we observed different interactive properties for different mixing ratios of these chemicals. These approaches for studying pesticide mixtures can improve evaluations of potential toxicity under varying experimental conditions that may mimic human exposures.

Atmospheric radiation modeling of galactic cosmic rays using LRO/CRaTER and the EMMREM model with comparisons to balloon and airline based measurements

NASA Astrophysics Data System (ADS)

Joyce, C. J.; Schwadron, N. A.; Townsend, L. W.; deWet, W. C.; Wilson, J. K.; Spence, H. E.; Tobiska, W. K.; Shelton-Mur, K.; Yarborough, A.; Harvey, J.; Herbst, A.; Koske-Phillips, A.; Molina, F.; Omondi, S.; Reid, C.; Reid, D.; Shultz, J.; Stephenson, B.; McDevitt, M.; Phillips, T.

2016-09-01

We provide an analysis of the galactic cosmic ray radiation environment of Earth's atmosphere using measurements from the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) aboard the Lunar Reconnaissance Orbiter (LRO) together with the Badhwar-O'Neil model and dose lookup tables generated by the Earth-Moon-Mars Radiation Environment Module (EMMREM). This study demonstrates an updated atmospheric radiation model that uses new dose tables to improve the accuracy of the modeled dose rates. Additionally, a method for computing geomagnetic cutoffs is incorporated into the model in order to account for location-dependent effects of the magnetosphere. Newly available measurements of atmospheric dose rates from instruments aboard commercial aircraft and high-altitude balloons enable us to evaluate the accuracy of the model in computing atmospheric dose rates. When compared to the available observations, the model seems to be reasonably accurate in modeling atmospheric radiation levels, overestimating airline dose rates by an average of 20%, which falls within the uncertainty limit recommended by the International Commission on Radiation Units and Measurements (ICRU). Additionally, measurements made aboard high-altitude balloons during simultaneous launches from New Hampshire and California provide an additional comparison to the model. We also find that the newly incorporated geomagnetic cutoff method enables the model to represent radiation variability as a function of location with sufficient accuracy.

From climate model ensembles to climate change impacts and adaptation: A case study of water resource management in the southwest of England

NASA Astrophysics Data System (ADS)

Lopez, Ana; Fung, Fai; New, Mark; Watts, Glenn; Weston, Alan; Wilby, Robert L.

2009-08-01

The majority of climate change impacts and adaptation studies so far have been based on at most a few deterministic realizations of future climate, usually representing different emissions scenarios. Large ensembles of climate models are increasingly available either as ensembles of opportunity or perturbed physics ensembles, providing a wealth of additional data that is potentially useful for improving adaptation strategies to climate change. Because of the novelty of this ensemble information, there is little previous experience of practical applications or of the added value of this information for impacts and adaptation decision making. This paper evaluates the value of perturbed physics ensembles of climate models for understanding and planning public water supply under climate change. We deliberately select water resource models that are already used by water supply companies and regulators on the assumption that uptake of information from large ensembles of climate models will be more likely if it does not involve significant investment in new modeling tools and methods. We illustrate the methods with a case study on the Wimbleball water resource zone in the southwest of England. This zone is sufficiently simple to demonstrate the utility of the approach but with enough complexity to allow a variety of different decisions to be made. Our research shows that the additional information contained in the climate model ensemble provides a better understanding of the possible ranges of future conditions, compared to the use of single-model scenarios. Furthermore, with careful presentation, decision makers will find the results from large ensembles of models more accessible and be able to more easily compare the merits of different management options and the timing of different adaptation. The overhead in additional time and expertise for carrying out the impacts analysis will be justified by the increased quality of the decision-making process. We remark that even though we have focused our study on a water resource system in the United Kingdom, our conclusions about the added value of climate model ensembles in guiding adaptation decisions can be generalized to other sectors and geographical regions.

Modelling Mass Movements for Planetary Studies

NASA Technical Reports Server (NTRS)

Bulmer, M. H.; Glaze, L.; Barnouin-Jha, O.; Murphy, W.; Neumann, G.

2002-01-01

Use of an empirical model in conjunction with data from the Chaos Jumbles rock avalanches constrain to first order their flow behavior, and provide a method to interpret rock/debris avalanche emplacement on Mars. Additional information is contained in the original extended abstract.

Children's Eating Attitudes and Behaviour: A Study of the Modelling and Control Theories of Parental Influence

ERIC Educational Resources Information Center

Brown, Rachael; Ogden, Jane

2004-01-01

The present study compared the modelling and control theories of parental influence on children's eating attitudes and behaviour with a focus on snack foods. Matched questionnaires describing reported snack intake, eating motivations and body dissatisfaction were completed by 112 parent/child pairs. Parents completed additional items relating to…

Cyberbullying and Cybervictimization within a Cross-Cultural Context: A Study of Canadian and Tanzanian Adolescents

ERIC Educational Resources Information Center

Shapka, Jennifer D.; Onditi, Hezron Z.; Collie, Rebecca J.; Lapidot-Lefler, Noam

2018-01-01

This study explored cyberbullying and cybervictimization (CBCV), for adolescents aged 11-15 from Tanzania (N = 426) and Canada (N = 592). Measurement invariance and model invariance was found for CBCV. In addition, multigroup structural equation modeling was used to explore several variables: age, gender, average hours online each day, accessing…

Perceptions of Usefulness: Using the Holland Code Theory, Multiple Intelligences Theory, and Role Model Identification to Determine a Career Niche in the Fashion Industry for First-Quarter Fashion Students

ERIC Educational Resources Information Center

Green, Crystal D.

2010-01-01

This action research study investigated the perceptions that student participants had on the development of a career exploration model and a career exploration project. The Holland code theory was the primary assessment used for this research study, in addition to the Multiple Intelligences theory and the identification of a role model for the…

Method for Designing Electronic Assemblies without Potting for Gun Launched Applications Through the Use of Additive Manufacturing

DTIC Science & Technology

2016-12-01

easily would be preferred. Many studies have been conducted to model the effects of potting materials on PCBs and their components: two such studies ...catch (SCAT) gun Guidance electronics On -board recorder (OBR) Precision guided munition (PGM) 16. SECURITY CLASSIFICATION OF: 17... On -board Recorder 2 Initial Method - Modeling Assumptions 2 Initial Method - Parts, Instances, and Simplifications in the Model 3 Initial Method

Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

PubMed

Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

2015-03-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

PubMed Central

Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

2015-01-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

Impact of Chemical Proportions on the Acute Neurotoxicity of a Mixture of Seven Carbamates in Preweanling and Adult Rats

EPA Science Inventory

Statistical design and environmental relevance are important aspects of studies of chemical mixtures, such as pesticides. We used a dose-additivity model to test experimentally the default assumptions of dose-additivity for two mixtures of seven N-methylcarbamates (carbaryl, carb...

Benchmarking DoD Use of Additive Manufacturing and Quantifying Costs

DTIC Science & Technology

2017-03-01

46 VI. Cost Benefit ...developing a cost model. The US Army Logistics Innovation Agency published a study called “Additive Manufacturing Cost - Benefit Analysis”. This...to over fifteen thousand dollars on GSA Advantage. Desktop printers do not require extensive support equipment. 47    VI. Cost Benefit

Analysis Of Resistance And Effective Wake Friction Due To Addition Of Stern Tunnels On Passenger Ship Using Cfd

NASA Astrophysics Data System (ADS)

Chrismianto, D.; Tuswan; Manik, P.

2018-03-01

In this study, the stern tunnel to improve the efficiency of ship propulsion system is analysed. Stern tunnels installed on the two sides of the ship stern. Analysis of ship resistance and wake friction of the ship using CFD are carried out. The stern tunnel height (Hw) and length (L) are implemented to find the better stern tunnel form of the ship. The result of analysis showed that model has a high stern tunnels (Hw) of 1,444 m or additional high stern tunnels ratio of 16% and stern long tunnels (L) about 7 m is a model that has the smallest resistance about 1.1137 N or able to make reduction of resistance amount 11.2582%. While, the model with the addition of height of 0.2 m and a length of 9 m of stern tunnel is a model that has the better advanced speed about 4,927% in increase, and better wake friction about 30.4% in reduce.

The effect of different levels of sunflower head pith addition on the properties of model system emulsions prepared from fresh and frozen beef.

PubMed

Sariçoban, Cemalettin; Yilmaz, Mustafa Tahsin; Karakaya, Mustafa; Tiske, Sümeyra Sultan

2010-01-01

The effect of sunflower head pith on the functional properties of emulsions was studied by using a model system. Oil/water (O/W) model emulsion systems were prepared from fresh and frozen beef by the addition of the pith at five concentrations. Emulsion capacity (EC), stability (ES), viscosity (EV), colour and flow properties of the prepared model system emulsions were analyzed. The pith addition increased the EC and ES and the highest EC and ES values were reached when 5% of pith added; however, further increase in the pith concentration caused an inverse trend in these values. Fresh beef emulsions had higher EC and ES values than did frozen beef emulsions. One percent pith concentration was the critic level for the EV values of fresh beef emulsions. EV values of the emulsions reached a maximum level at 5% pith level, followed by a decrease at 7% pit level.

Revisit of the Saito-Dresselhaus-Dresselhaus C2 ingestion model: on the mechanism of atomic-carbon-participated fullerene growth.

PubMed

Wang, Wei-Wei; Dang, Jing-Shuang; Zhao, Xiang; Nagase, Shigeru

2017-11-09

We introduce a mechanistic study based on a controversial fullerene bottom-up growth model proposed by R. Saito, G. Dresselhaus, and M. S. Dresselhaus. The so-called SDD C 2 addition model has been dismissed as chemically inadmissible but here we prove that it is feasible via successive atomic-carbon-participated addition and migration reactions. Kinetic calculations on the formation of isolated pentagon rule (IPR)-obeying C 70 and Y 3 N@C 80 are carried out by employing the SDD model for the first time. A stepwise mechanism is proposed with a considerably low barrier of ca. 2 eV which is about 3 eV lower than a conventional isomerization-containing fullerene growth pathway.

Modeling mixtures of thyroid gland function disruptors in a vertebrate alternative model, the zebrafish eleutheroembryo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thienpont, Benedicte; Barata, Carlos; Raldúa, Demetrio, E-mail: drpqam@cid.csic.es

2013-06-01

Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study usedmore » the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO{sub 4} (NIS-inhibitor) dosed at a fixed ratio of EC{sub 10} that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of mixtures of goitrogens.« less

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

NASA Technical Reports Server (NTRS)

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-01-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data.

PubMed

Kloog, Itai; Chudnovsky, Alexandra A; Just, Allan C; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-10-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM 2.5 ) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM 2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM 2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R 2 =0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R 2 =0.87, R 2 =0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

PubMed Central

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2017-01-01

Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. Methods We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003–2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region. PMID:28966552

Average inactivity time model, associated orderings and reliability properties

NASA Astrophysics Data System (ADS)

Kayid, M.; Izadkhah, S.; Abouammoh, A. M.

2018-02-01

In this paper, we introduce and study a new model called 'average inactivity time model'. This new model is specifically applicable to handle the heterogeneity of the time of the failure of a system in which some inactive items exist. We provide some bounds for the mean average inactivity time of a lifespan unit. In addition, we discuss some dependence structures between the average variable and the mixing variable in the model when original random variable possesses some aging behaviors. Based on the conception of the new model, we introduce and study a new stochastic order. Finally, to illustrate the concept of the model, some interesting reliability problems are reserved.

What You Don't Know Can Hurt You: Missing Data and Partial Credit Model Estimates

PubMed Central

Thomas, Sarah L.; Schmidt, Karen M.; Erbacher, Monica K.; Bergeman, Cindy S.

2017-01-01

The authors investigated the effect of Missing Completely at Random (MCAR) item responses on partial credit model (PCM) parameter estimates in a longitudinal study of Positive Affect. Participants were 307 adults from the older cohort of the Notre Dame Study of Health and Well-Being (Bergeman and Deboeck, 2014) who completed questionnaires including Positive Affect items for 56 days. Additional missing responses were introduced to the data, randomly replacing 20%, 50%, and 70% of the responses on each item and each day with missing values, in addition to the existing missing data. Results indicated that item locations and person trait level measures diverged from the original estimates as the level of degradation from induced missing data increased. In addition, standard errors of these estimates increased with the level of degradation. Thus, MCAR data does damage the quality and precision of PCM estimates. PMID:26784376

Mobile Integrated Health Care and Community Paramedicine: An Emerging Emergency Medical Services Concept.

PubMed

Choi, Bryan Y; Blumberg, Charles; Williams, Kenneth

2016-03-01

Mobile integrated health care and community paramedicine are models of health care delivery that use emergency medical services (EMS) personnel to fill gaps in local health care infrastructure. Community paramedics may perform in an expanded role and require additional training in the management of chronic disease, communication skills, and cultural sensitivity, whereas other models use all levels of EMS personnel without additional training. Currently, there are few studies of the efficacy, safety, and cost-effectiveness of mobile integrated health care and community paramedicine programs. Observations from existing program data suggest that these systems may prevent congestive heart failure readmissions, reduce EMS frequent-user transports, and reduce emergency department visits. Additional studies are needed to support the clinical and economic benefit of mobile integrated health care and community paramedicine. Copyright © 2015 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

CO2 enrichment and N addition increase nutrient loss from decomposing leaf litter in subtropical model forest ecosystems

PubMed Central

Liu, Juxiu; Fang, Xiong; Deng, Qi; Han, Tianfeng; Huang, Wenjuan; Li, Yiyong

2015-01-01

As atmospheric CO2 concentration increases, many experiments have been carried out to study effects of CO2 enrichment on litter decomposition and nutrient release. However, the result is still uncertain. Meanwhile, the impact of CO2 enrichment on nutrients other than N and P are far less studied. Using open-top chambers, we examined effects of elevated CO2 and N addition on leaf litter decomposition and nutrient release in subtropical model forest ecosystems. We found that both elevated CO2 and N addition increased nutrient (C, N, P, K, Ca, Mg and Zn) loss from the decomposing litter. The N, P, Ca and Zn loss was more than tripled in the chambers exposed to both elevated CO2 and N addition than those in the control chambers after 21 months of treatment. The stimulation of nutrient loss under elevated CO2 was associated with the increased soil moisture, the higher leaf litter quality and the greater soil acidity. Accelerated nutrient release under N addition was related to the higher leaf litter quality, the increased soil microbial biomass and the greater soil acidity. Our results imply that elevated CO2 and N addition will increase nutrient cycling in subtropical China under the future global change. PMID:25608664

Additional Samples: Where They Should Be Located

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pilger, G. G., E-mail: jfelipe@ufrgs.br; Costa, J. F. C. L.; Koppe, J. C.

2001-09-15

Information for mine planning requires to be close spaced, if compared to the grid used for exploration and resource assessment. The additional samples collected during quasimining usually are located in the same pattern of the original diamond drillholes net but closer spaced. This procedure is not the best in mathematical sense for selecting a location. The impact of an additional information to reduce the uncertainty about the parameter been modeled is not the same everywhere within the deposit. Some locations are more sensitive in reducing the local and global uncertainty than others. This study introduces a methodology to select additionalmore » sample locations based on stochastic simulation. The procedure takes into account data variability and their spatial location. Multiple equally probable models representing a geological attribute are generated via geostatistical simulation. These models share basically the same histogram and the same variogram obtained from the original data set. At each block belonging to the model a value is obtained from the n simulations and their combination allows one to access local variability. Variability is measured using an uncertainty index proposed. This index was used to map zones of high variability. A value extracted from a given simulation is added to the original data set from a zone identified as erratic in the previous maps. The process of adding samples and simulation is repeated and the benefit of the additional sample is evaluated. The benefit in terms of uncertainty reduction is measure locally and globally. The procedure showed to be robust and theoretically sound, mapping zones where the additional information is most beneficial. A case study in a coal mine using coal seam thickness illustrates the method.« less

External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

PubMed

Hickey, Graeme L; Blackstone, Eugene H

2016-08-01

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Determinants of fast food consumption among Iranian high school students based on planned behavior theory.

PubMed

Sharifirad, Gholamreza; Yarmohammadi, Parastoo; Azadbakht, Leila; Morowatisharifabad, Mohammad Ali; Hassanzadeh, Akbar

2013-01-01

This study was conducted to identify some factors (beliefs and norms) which are related to fast food consumption among high school students in Isfahan, Iran. We used the framework of the theory planned behavior (TPB) to predict this behavior. Cross-sectional data were available from high school students (n = 521) who were recruited by cluster randomized sampling. All of the students completed a questionnaire assessing variables of standard TPB model including attitude, subjective norms, perceived behavior control (PBC), and the additional variables past behavior, actual behavior control (ABC). The TPB variables explained 25.7% of the variance in intentions with positive attitude as the strongest (β = 0.31, P < 0.001) and subjective norms as the weakest (β = 0.29, P < 0.001) determinant. Concurrently, intentions accounted for 6% of the variance for fast food consumption. Past behavior and ABC accounted for an additional amount of 20.4% of the variance in fast food consumption. Overall, the present study suggests that the TPB model is useful in predicting related beliefs and norms to the fast food consumption among adolescents. Subjective norms in TPB model and past behavior in TPB model with additional variables (past behavior and actual behavior control) were the most powerful predictors of fast food consumption. Therefore, TPB model may be a useful framework for planning intervention programs to reduce fast food consumption by students.

Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer.

PubMed

Rauh, C; Hack, C C; Häberle, L; Hein, A; Engel, A; Schrauder, M G; Fasching, P A; Jud, S M; Ekici, A B; Loehberg, C R; Meier-Meitinger, M; Ozan, S; Schulz-Wendtland, R; Uder, M; Hartmann, A; Wachter, D L; Beckmann, M W; Heusinger, K

2012-08-01

Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study with hospital-based patients with a diagnosis of invasive breast cancer and healthy women as controls. A total of 561 patients and 376 controls with available mammographic density were included into this study. We describe the differences concerning the common risk factors BMI, parital status, use of hormone replacement therapy (HRT) and menopause between cases and controls and estimate the odds ratios for PMD and DA, adjusted for the mentioned risk factors. Furthermore we compare the prediction models with each other to find out whether the addition of DA improves the model. Results: Mammographic density and DA were highly correlated with each other. Both variables were as well correlated to the commonly known risk factors with an expected direction and strength, however PMD (ρ = -0.56) was stronger correlated to BMI than DA (ρ = -0.11). The group of women within the highest quartil of PMD had an OR of 2.12 (95 % CI: 1.25-3.62). This could not be seen for the fourth quartile concerning DA. However the assessment of breast cancer risk could be improved by including DA in a prediction model in addition to common risk factors and PMD. Conclusions: The inclusion of the parameter DA into a prediction model for breast cancer in addition to established risk factors and PMD could improve the breast cancer risk assessment. As DA is measured together with PMD in the process of computer-assisted assessment of PMD it might be considered to include it as one additional breast cancer risk factor that is obtained from breast imaging.

A pharmacometric case study regarding the sensitivity of structural model parameter estimation to error in patient reported dosing times.

PubMed

Knights, Jonathan; Rohatagi, Shashank

2015-12-01

Although there is a body of literature focused on minimizing the effect of dosing inaccuracies on pharmacokinetic (PK) parameter estimation, most of the work centers on missing doses. No attempt has been made to specifically characterize the effect of error in reported dosing times. Additionally, existing work has largely dealt with cases in which the compound of interest is dosed at an interval no less than its terminal half-life. This work provides a case study investigating how error in patient reported dosing times might affect the accuracy of structural model parameter estimation under sparse sampling conditions when the dosing interval is less than the terminal half-life of the compound, and the underlying kinetics are monoexponential. Additional effects due to noncompliance with dosing events are not explored and it is assumed that the structural model and reasonable initial estimates of the model parameters are known. Under the conditions of our simulations, with structural model CV % ranging from ~20 to 60 %, parameter estimation inaccuracy derived from error in reported dosing times was largely controlled around 10 % on average. Given that no observed dosing was included in the design and sparse sampling was utilized, we believe these error results represent a practical ceiling given the variability and parameter estimates for the one-compartment model. The findings suggest additional investigations may be of interest and are noteworthy given the inability of current PK software platforms to accommodate error in dosing times.

FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model

PubMed Central

Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

2014-01-01

A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well. PMID:25484854

Model for Assembly Line Re-Balancing Considering Additional Capacity and Outsourcing to Face Demand Fluctuations

NASA Astrophysics Data System (ADS)

Samadhi, TMAA; Sumihartati, Atin

2016-02-01

The most critical stage in a garment industry is sewing process, because generally, it consists of a number of operations and a large number of sewing machines for each operation. Therefore, it requires a balancing method that can assign task to work station with balance workloads. Many studies on assembly line balancing assume a new assembly line, but in reality, due to demand fluctuation and demand increased a re-balancing is needed. To cope with those fluctuating demand changes, additional capacity can be carried out by investing in spare sewing machine and paying for sewing service through outsourcing. This study develops an assembly line balancing (ALB) model on existing line to cope with fluctuating demand change. Capacity redesign is decided if the fluctuation demand exceeds the available capacity through a combination of making investment on new machines and outsourcing while considering for minimizing the cost of idle capacity in the future. The objective of the model is to minimize the total cost of the line assembly that consists of operating costs, machine cost, adding capacity cost, losses cost due to idle capacity and outsourcing costs. The model develop is based on an integer programming model. The model is tested for a set of data of one year demand with the existing number of sewing machines of 41 units. The result shows that additional maximum capacity up to 76 units of machine required when there is an increase of 60% of the average demand, at the equal cost parameters..

CHARACTERIZING THE DISPERSIVE STATE OF CONVECTIVE BOUNDARY LAYERS FOR APPLIED DISPERSION MODELING

EPA Science Inventory

Estimates from semiempirical models that characterize surface heat flux, mixing depth, and profiles of temperature, wind, and turbulence are compared with observations from atmospheric field Studies conducted in Colorado, Illinois, Indiana, and Minnesota. In addition, for wind an...

Establishment and Characterization of an Air-Liquid Canine Corneal Organ Culture Model To Study Acute Herpes Keratitis

PubMed Central

Harman, Rebecca M.; Bussche, Leen; Ledbetter, Eric C.

2014-01-01

ABSTRACT Despite the clinical importance of herpes simplex virus (HSV)-induced ocular disease, the underlying pathophysiology of the disease remains poorly understood, in part due to the lack of adequate virus–natural-host models in which to study the cellular and viral factors involved in acute corneal infection. We developed an air-liquid canine corneal organ culture model and evaluated its susceptibility to canine herpesvirus type 1 (CHV-1) in order to study ocular herpes in a physiologically relevant natural host model. Canine corneas were maintained in culture at an air-liquid interface for up to 25 days, and no degenerative changes were observed in the corneal epithelium during cultivation using histology for morphometric analyses, terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling (TUNEL) assays, and transmission electron microscopy (TEM). Next, canine corneas were inoculated with CHV-1 for 48 h, and at that time point postinfection, viral plaques could be visualized in the corneal epithelium and viral DNA copies were detected in both the infected corneas and culture supernatants. In addition, we found that canine corneas produced proinflammatory cytokines in response to CHV-1 infection similarly to what has been described for HSV-1. This emphasizes the value of our model as a virus–natural-host model to study ocular herpesvirus infections. IMPORTANCE This study is the first to describe the establishment of an air-liquid canine corneal organ culture model as a useful model to study ocular herpesvirus infections. The advantages of this physiologically relevant model include the fact that (i) it provides a system in which ocular herpes can be studied in a virus–natural-host setting and (ii) it reduces the number of experimental animals needed. In addition, this long-term explant culture model may also facilitate research in other fields where noninfectious and infectious ocular diseases of dogs and humans are being studied. PMID:25231295

On the potential of models for location and scale for genome-wide DNA methylation data

PubMed Central

2014-01-01

Background With the help of epigenome-wide association studies (EWAS), increasing knowledge on the role of epigenetic mechanisms such as DNA methylation in disease processes is obtained. In addition, EWAS aid the understanding of behavioral and environmental effects on DNA methylation. In terms of statistical analysis, specific challenges arise from the characteristics of methylation data. First, methylation β-values represent proportions with skewed and heteroscedastic distributions. Thus, traditional modeling strategies assuming a normally distributed response might not be appropriate. Second, recent evidence suggests that not only mean differences but also variability in site-specific DNA methylation associates with diseases, including cancer. The purpose of this study was to compare different modeling strategies for methylation data in terms of model performance and performance of downstream hypothesis tests. Specifically, we used the generalized additive models for location, scale and shape (GAMLSS) framework to compare beta regression with Gaussian regression on raw, binary logit and arcsine square root transformed methylation data, with and without modeling a covariate effect on the scale parameter. Results Using simulated and real data from a large population-based study and an independent sample of cancer patients and healthy controls, we show that beta regression does not outperform competing strategies in terms of model performance. In addition, Gaussian models for location and scale showed an improved performance as compared to models for location only. The best performance was observed for the Gaussian model on binary logit transformed β-values, referred to as M-values. Our results further suggest that models for location and scale are specifically sensitive towards violations of the distribution assumption and towards outliers in the methylation data. Therefore, a resampling procedure is proposed as a mode of inference and shown to diminish type I error rate in practically relevant settings. We apply the proposed method in an EWAS of BMI and age and reveal strong associations of age with methylation variability that are validated in an independent sample. Conclusions Models for location and scale are promising tools for EWAS that may help to understand the influence of environmental factors and disease-related phenotypes on methylation variability and its role during disease development. PMID:24994026

Digital control analysis and design of a field-sensed magnetic suspension system.

PubMed

Li, Jen-Hsing; Chiou, Juing-Shian

2015-03-13

Magnetic suspension systems are mechatronic systems and crucial in several engineering applications, such as the levitation of high-speed trains, frictionless bearings, and wind tunnels. Magnetic suspension systems are nonlinear and unstable systems; therefore, they are suitable educational benchmarks for testing various modeling and control methods. This paper presents the digital modeling and control of magnetic suspension systems. First, the magnetic suspension system is stabilized using a digital proportional-derivative controller. Subsequently, the digital model is identified using recursive algorithms. Finally, a digital mixed linear quadratic regulator (LQR)/H∞ control is adopted to stabilize the magnetic suspension system robustly. Simulation examples and a real-world example are provided to demonstrate the practicality of the study results. In this study, a digital magnetic suspension system model was developed and reviewed. In addition, equivalent state and output feedback controls for magnetic suspension systems were developed. Using this method, the controller design for magnetic suspension systems was simplified, which is the novel contribution of this study. In addition, this paper proposes a complete digital controller design procedure for magnetic suspension systems.

Venus Global Reference Atmospheric Model Status and Planned Updates

NASA Technical Reports Server (NTRS)

Justh, H. L.; Dwyer Cianciolo, A. M.

2017-01-01

The Venus Global Reference Atmospheric Model (Venus-GRAM) was originally developed in 2004 under funding from NASA's In Space Propulsion (ISP) Aerocapture Project to support mission studies at the planet. Many proposals, including NASA New Frontiers and Discovery, as well as other studies have used Venus-GRAM to design missions and assess system robustness. After Venus-GRAM's release in 2005, several missions to Venus have generated a wealth of additional atmospheric data, yet few model updates have been made to Venus-GRAM. This paper serves to address three areas: (1) to present the current status of Venus-GRAM, (2) to identify new sources of data and other upgrades that need to be incorporated to maintain Venus-GRAM credibility and (3) to identify additional Venus-GRAM options and features that could be included to increase its capability. This effort will de-pend on understanding the needs of the user community, obtaining new modeling data and establishing a dedicated funding source to support continual up-grades. This paper is intended to initiate discussion that can result in an upgraded and validated Venus-GRAM being available to future studies and NASA proposals.

Vapor intrusion risk of fuel ether oxygenates methyl tert-butyl ether (MTBE), tert-amyl methyl ether (TAME) and ethyl tert-butyl ether (ETBE): A modeling study.

PubMed

Ma, Jie; Xiong, Desen; Li, Haiyan; Ding, Yi; Xia, Xiangcheng; Yang, Yongqi

2017-06-15

Vapor intrusion of synthetic fuel additives represents a critical yet still neglected problem at sites contaminated by petroleum fuel releases. This study used an advanced numerical model to investigate the vapor intrusion potential of fuel ether oxygenates methyl tert-butyl ether (MTBE), tert-amyl methyl ether (TAME), and ethyl tert-butyl ether (ETBE). Simulated indoor air concentration of these compounds can exceed USEPA indoor air screening level for MTBE (110μg/m 3 ). Our results also reveal that MTBE has much higher chance to cause vapor intrusion problems than TAME and ETBE. This study supports the statements made by USEPA in the Petroleum Vapor Intrusion (PVI) Guidance that the vertical screening criteria for petroleum hydrocarbons may not provide sufficient protectiveness for fuel additives, and ether oxygenates in particular. In addition to adverse impacts on human health, ether oxygenate vapor intrusion may also cause aesthetic problems (i.e., odour and flavour). Overall, this study points out that ether oxygenates can cause vapor intrusion problems. We recommend that USEPA consider including the field measurement data of synthetic fuel additives in the existing PVI database and possibly revising the PVI Guidance as necessary. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison between a new model and current models for estimating trunk segment inertial parameters.

PubMed

Wicke, Jason; Dumas, Genevieve A; Costigan, Patrick A

2009-01-05

Modeling of the body segments to estimate segment inertial parameters is required in the kinetic analysis of human motion. A new geometric model for the trunk has been developed that uses various cross-sectional shapes to estimate segment volume and adopts a non-uniform density function that is gender-specific. The goal of this study was to test the accuracy of the new model for estimating the trunk's inertial parameters by comparing it to the more current models used in biomechanical research. Trunk inertial parameters estimated from dual X-ray absorptiometry (DXA) were used as the standard. Twenty-five female and 24 male college-aged participants were recruited for the study. Comparisons of the new model to the accepted models were accomplished by determining the error between the models' trunk inertial estimates and that from DXA. Results showed that the new model was more accurate across all inertial estimates than the other models. The new model had errors within 6.0% for both genders, whereas the other models had higher average errors ranging from 10% to over 50% and were much more inconsistent between the genders. In addition, there was little consistency in the level of accuracy for the other models when estimating the different inertial parameters. These results suggest that the new model provides more accurate and consistent trunk inertial estimates than the other models for both female and male college-aged individuals. However, similar studies need to be performed using other populations, such as elderly or individuals from a distinct morphology (e.g. obese). In addition, the effect of using different models on the outcome of kinetic parameters, such as joint moments and forces needs to be assessed.

The linear relationship between the Vulnerable Elders Survey-13 score and mortality in an Asian population of community-dwelling older persons.

PubMed

Wang, Jye; Lin, Wender; Chang, Ling-Hui

2018-01-01

The Vulnerable Elders Survey-13 (VES-13) has been used as a screening tool to identify vulnerable community-dwelling older persons for more in-depth assessment and targeted interventions. Although many studies supported its use in different populations, few have addressed Asian populations. The optimal scaling system for the VES-13 in predicting health outcomes also has not been adequately tested. This study (1) assesses the applicability of the VES-13 to predict the mortality of community-dwelling older persons in Taiwan, (2) identifies the best scaling system for the VES-13 in predicting mortality using generalized additive models (GAMs), and (3) determines whether including covariates, such as socio-demographic factors and common geriatric syndromes, improves model fitting. This retrospective longitudinal cohort study analyzed the data of 2184 community-dwelling persons 65 years old or older from the 2003 wave of the national-wide Taiwan Longitudinal Study on Aging. Cox proportional hazards models and Generalized Additive Models (GAMs) were used. The VES-13 significantly predicted the mortality of Taiwan's community-dwelling elders. A one-point increase in the VES-13 score raised the risk of death by 26% (hazard ratio, 1.26; 95% confidence interval, 1.21-1.32). The hazard ratio of death increased linearly with each additional VES-13 score point, suggesting that using a continuous scale is appropriate. Inclusion of socio-demographic factors and geriatric syndromes improved the model-fitting. The VES-13 is appropriate for an Asian population. VES-13 scores linearly predict the mortality of this population. Adjusting the weighting of the physical activity items may improve the performance of the VES-13. Copyright © 2017 Elsevier B.V. All rights reserved.

The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism.

PubMed

Birkel, Garrett W; Ghosh, Amit; Kumar, Vinay S; Weaver, Daniel; Ando, David; Backman, Tyler W H; Arkin, Adam P; Keasling, Jay D; Martín, Héctor García

2017-04-05

Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13 C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.

The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

DOE PAGES

Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.; ...

2017-04-05

Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics,more » proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13C Metabolic Flux Analysis (2S- 13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.« less

The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.

Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics,more » proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13C Metabolic Flux Analysis (2S- 13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.« less

Naturally light Dirac neutrino in Left-Right Symmetric Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Borah, Debasish; Dasgupta, Arnab, E-mail: dborah@iitg.ernet.in, E-mail: arnab.d@iopb.res.in

We study the possibility of generating tiny Dirac masses of neutrinos in Left-Right Symmetric Model (LRSM) without requiring the existence of any additional symmetries. The charged fermions acquire masses through a universal seesaw mechanism due to the presence of additional vector like fermions. The neutrinos acquire a one-loop Dirac mass from the same additional vector like charged leptons without requiring any additional discrete symmetries. The model can also be extended by an additional Z {sub 2} symmetry in order to have a scotogenic version of this scenario predicting a stable dark matter candidate. We show that the latest Planck uppermore » bound on the effective number of relativistic degrees of freedom N {sub eff}=3.15 ± 0.23 tightly constrains the right sector gauge boson masses to be heavier than 3.548 TeV . This bound on gauge boson mass also affects the allowed values of right scalar doublet dark matter mass from the requirement of satisfying the Planck bound on dark matter relic abundance. We also discuss the possible implications of such a scenario in charged lepton flavour violation and generating observable electric dipole moment of leptons.« less

Development of a Three-Dimensional, Unstructured Material Response Design Tool

NASA Technical Reports Server (NTRS)

Schulz, Joseph C.; Stern, Eric C.; Muppidi, Suman; Palmer, Grant E.; Schroeder, Olivia

2017-01-01

A preliminary verification and validation of a new material response model is presented. This model, Icarus, is intended to serve as a design tool for the thermal protection systems of re-entry vehicles. Currently, the capability of the model is limited to simulating the pyrolysis of a material as a result of the radiative and convective surface heating imposed on the material from the surrounding high enthalpy gas. Since the major focus behind the development of Icarus has been model extensibility, the hope is that additional physics can be quickly added. This extensibility is critical since thermal protection systems are becoming increasing complex, e.g. woven carbon polymers. Additionally, as a three-dimensional, unstructured, finite-volume model, Icarus is capable of modeling complex geometries. In this paper, the mathematical and numerical formulation is presented followed by a discussion of the software architecture and some preliminary verification and validation studies.

Quantum vision in three dimensions

NASA Astrophysics Data System (ADS)

Roth, Yehuda

We present four models for describing a 3-D vision. Similar to the mirror scenario, our models allow 3-D vision with no need for additional accessories such as stereoscopic glasses or a hologram film. These four models are based on brain interpretation rather than pure objective encryption. We consider the observer "subjective" selection of a measuring device and the corresponding quantum collapse into one of his selected states, as a tool for interpreting reality in according to the observer concepts. This is the basic concept of our study and it is introduced in the first model. Other models suggests "soften" versions that might be much easier to implement. Our quantum interpretation approach contribute to the following fields. In technology the proposed models can be implemented into real devices, allowing 3-D vision without additional accessories. Artificial intelligence: In the desire to create a machine that exchange information by using human terminologies, our interpretation approach seems to be appropriate.

AA9int: SNP Interaction Pattern Search Using Non-Hierarchical Additive Model Set.

PubMed

Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa; Tung, Heng-Yuan; Sellers, Thomas A; Pow-Sang, Julio; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Hamdy, Freddie; Neal, David E; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lu, Yong-Jie; Park, Jong Y

2018-06-07

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. hlin1@lsuhsc.edu. Supplementary data are available at Bioinformatics online.

Evaluating growth models: A case study using PrognosisBC

Treesearch

Peter Marshall; Pablo Parysow; Shadrach Akindele

2008-01-01

The ability of the PrognosisBC (Version 3.0) growth model to predict tree and stand growth was assessed against a series of remeasured permanent sample plots, including some which had been precommercially thinned. In addition, the model was evaluated for logical consistency across a variety of stand structures using simulation. By the end of the...

A Multiple Risk Factors Model of the Development of Aggression among Early Adolescents from Urban Disadvantaged Neighborhoods

ERIC Educational Resources Information Center

Kim, Sangwon; Orpinas, Pamela; Kamphaus, Randy; Kelder, Steven H.

2011-01-01

This study empirically derived a multiple risk factors model of the development of aggression among middle school students in urban, low-income neighborhoods, using Hierarchical Linear Modeling (HLM). Results indicated that aggression increased from sixth to eighth grade. Additionally, the influences of four risk domains (individual, family,…

Multilevel Modeling and School Psychology: A Review and Practical Example

ERIC Educational Resources Information Center

Graves, Scott L., Jr.; Frohwerk, April

2009-01-01

The purpose of this article is to provide an overview of the state of multilevel modeling in the field of school psychology. The authors provide a systematic assessment of published research of multilevel modeling studies in 5 journals devoted to the research and practice of school psychology. In addition, a practical example from the nationally…

A Dual-Process Approach to Health Risk Decision Making: The Prototype Willingness Model

ERIC Educational Resources Information Center

Gerrard, Meg; Gibbons, Frederick X.; Houlihan, Amy E.; Stock, Michelle L.; Pomery, Elizabeth A.

2008-01-01

Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their…

The valuation of currency options by fractional Brownian motion.

PubMed

Shokrollahi, Foad; Kılıçman, Adem

2016-01-01

This research aims to investigate a model for pricing of currency options in which value governed by the fractional Brownian motion model (FBM). The fractional partial differential equation and some Greeks are also obtained. In addition, some properties of our pricing formula and simulation studies are presented, which demonstrate that the FBM model is easy to use.

Gender Differences in Depressive Symptoms during Adolescence: The Contributions of Weight-Related Concerns and Behaviors

ERIC Educational Resources Information Center

Vaughan, Christine A.; Halpern, Carolyn T.

2010-01-01

A theoretical model of gender differences in depressive symptoms during adolescence was evaluated using data from Waves I and II of the National Longitudinal Study of Adolescent Health. The theoretical model under examination was primarily informed by the gender-additive model of gender differences in depressive symptoms during adolescence…

Assessing Psychological Symptoms and Well-Being: Application of a Dual-Factor Mental Health Model to Understand College Student Performance

ERIC Educational Resources Information Center

Antaramian, Susan

2015-01-01

A dual-factor mental health model includes measures of positive psychological well-being in addition to traditional indicators of psychopathology to comprehensively determine mental health status. The current study examined the utility of this model in understanding the psychological adjustment and educational functioning of college students. A…

Are we there yet? Tracking the development of new model systems

Treesearch

A. Abzhanov; C. Extavour; A. Groover; S. Hodges; H. Hoekstra; E. Kramer; A. Monteiro

2008-01-01

It is increasingly clear that additional ‘model’ systems are needed to elucidate the genetic and developmental basis of organismal diversity. Whereas model system development previously required enormous investment, recent advances including the decreasing cost of DNA sequencing and the power of reverse genetics to study gene function are greatly facilitating...

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

NASA Astrophysics Data System (ADS)

Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

Orbital-selective Mott phases of a one-dimensional three-orbital Hubbard model studied using computational techniques

DOE PAGES

Liu, Guangkun; Kaushal, Nitin; Liu, Shaozhi; ...

2016-06-24

A recently introduced one-dimensional three-orbital Hubbard model displays orbital-selective Mott phases with exotic spin arrangements such as spin block states [J. Rincón et al., Phys. Rev. Lett. 112, 106405 (2014)]. In this paper we show that the constrained-path quantum Monte Carlo (CPQMC) technique can accurately reproduce the phase diagram of this multiorbital one-dimensional model, paving the way to future CPQMC studies in systems with more challenging geometries, such as ladders and planes. The success of this approach relies on using the Hartree-Fock technique to prepare the trial states needed in CPQMC. In addition, we study a simplified version of themore » model where the pair-hopping term is neglected and the Hund coupling is restricted to its Ising component. The corresponding phase diagrams are shown to be only mildly affected by the absence of these technically difficult-to-implement terms. This is confirmed by additional density matrix renormalization group and determinant quantum Monte Carlo calculations carried out for the same simplified model, with the latter displaying only mild fermion sign problems. Lastly, we conclude that these methods are able to capture quantitatively the rich physics of the several orbital-selective Mott phases (OSMP) displayed by this model, thus enabling computational studies of the OSMP regime in higher dimensions, beyond static or dynamic mean-field approximations.« less

Clinical profiles associated with influenza disease in the ferret model.

PubMed

Stark, Gregory V; Long, James P; Ortiz, Diana I; Gainey, Melicia; Carper, Benjamin A; Feng, Jingyu; Miller, Stephen M; Bigger, John E; Vela, Eric M

2013-01-01

Influenza A viruses continue to pose a threat to human health; thus, various vaccines and prophylaxis continue to be developed. Testing of these products requires various animal models including mice, guinea pigs, and ferrets. However, because ferrets are naturally susceptible to infection with human influenza viruses and because the disease state resembles that of human influenza, these animals have been widely used as a model to study influenza virus pathogenesis. In this report, a statistical analysis was performed to evaluate data involving 269 ferrets infected with seasonal influenza, swine influenza, and highly pathogenic avian influenza (HPAI) from 16 different studies over a five year period. The aim of the analyses was to better qualify the ferret model by identifying relationships among important animal model parameters (endpoints) and variables of interest, which include survival, time-to-death, changes in body temperature and weight, and nasal wash samples containing virus, in addition to significant changes from baseline in selected hematology and clinical chemistry parameters. The results demonstrate that a disease clinical profile, consisting of various changes in the biological parameters tested, is associated with various influenza A infections in ferrets. Additionally, the analysis yielded correlates of protection associated with HPAI disease in ferrets. In all, the results from this study further validate the use of the ferret as a model to study influenza A pathology and to evaluate product efficacy.

Client satisfaction with reproductive health-care quality: integrating business approaches to modeling and measurement.

PubMed

Alden, Dana L; Do, Mai Hoa; Bhawuk, Dharm

2004-12-01

Health-care managers are increasingly interested in client perceptions of clinic service quality and satisfaction. While tremendous progress has occurred, additional perspectives on the conceptualization, modeling and measurement of these constructs may further assist health-care managers seeking to provide high-quality care. To that end, this study draws on theories from business and health to develop an integrated model featuring antecedents to and consequences of reproductive health-care client satisfaction. In addition to developing a new model, this study contributes by testing how well Western-based theories of client satisfaction hold in a developing, Asian country. Applied to urban, reproductive health clinic users in Hanoi, Vietnam, test results suggest that hypothesized antecedents such as pre-visit expectations, perceived clinic performance and how much performance exceeds expectations impact client satisfaction. However, the relative importance of these predictors appears to vary depending on a client's level of service-related experience. Finally, higher levels of client satisfaction are positively related to future clinic use intentions. This study demonstrates the value of: (1) incorporating theoretical perspectives from multiple disciplines to model processes underlying health-care satisfaction and (2) field testing those models before implementation. It also furthers research designed to provide health-care managers with actionable measures of the complex processes related to their clients' satisfaction.

Computational study of single-expansion-ramp nozzles with external burning

NASA Astrophysics Data System (ADS)

Yungster, Shaye; Trefny, Charles J.

1992-04-01

A computational investigation of the effects of external burning on the performance of single expansion ramp nozzles (SERN) operating at transonic speeds is presented. The study focuses on the effects of external heat addition and introduces a simplified injection and mixing model based on a control volume analysis. This simplified model permits parametric and scaling studies that would have been impossible to conduct with a detailed CFD analysis. The CFD model is validated by comparing the computed pressure distribution and thrust forces, for several nozzle configurations, with experimental data. Specific impulse calculations are also presented which indicate that external burning performance can be superior to other methods of thrust augmentation at transonic speeds. The effects of injection fuel pressure and nozzle pressure ratio on the performance of SERN nozzles with external burning are described. The results show trends similar to those reported in the experimental study, and provide additional information that complements the experimental data, improving our understanding of external burning flowfields. A study of the effect of scale is also presented. The results indicate that combustion kinetics do not make the flowfield sensitive to scale.

Computational study of single-expansion-ramp nozzles with external burning

NASA Technical Reports Server (NTRS)

Yungster, Shaye; Trefny, Charles J.

1992-01-01

A computational investigation of the effects of external burning on the performance of single expansion ramp nozzles (SERN) operating at transonic speeds is presented. The study focuses on the effects of external heat addition and introduces a simplified injection and mixing model based on a control volume analysis. This simplified model permits parametric and scaling studies that would have been impossible to conduct with a detailed CFD analysis. The CFD model is validated by comparing the computed pressure distribution and thrust forces, for several nozzle configurations, with experimental data. Specific impulse calculations are also presented which indicate that external burning performance can be superior to other methods of thrust augmentation at transonic speeds. The effects of injection fuel pressure and nozzle pressure ratio on the performance of SERN nozzles with external burning are described. The results show trends similar to those reported in the experimental study, and provide additional information that complements the experimental data, improving our understanding of external burning flowfields. A study of the effect of scale is also presented. The results indicate that combustion kinetics do not make the flowfield sensitive to scale.

GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures.

PubMed

Urbanowicz, Ryan J; Kiralis, Jeff; Sinnott-Armstrong, Nicholas A; Heberling, Tamra; Fisher, Jonathan M; Moore, Jason H

2012-10-01

Geneticists who look beyond single locus disease associations require additional strategies for the detection of complex multi-locus effects. Epistasis, a multi-locus masking effect, presents a particular challenge, and has been the target of bioinformatic development. Thorough evaluation of new algorithms calls for simulation studies in which known disease models are sought. To date, the best methods for generating simulated multi-locus epistatic models rely on genetic algorithms. However, such methods are computationally expensive, difficult to adapt to multiple objectives, and unlikely to yield models with a precise form of epistasis which we refer to as pure and strict. Purely and strictly epistatic models constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. This makes them an attractive gold standard for simulation studies considering complex multi-locus effects. We introduce GAMETES, a user-friendly software package and algorithm which generates complex biallelic single nucleotide polymorphism (SNP) disease models for simulation studies. GAMETES rapidly and precisely generates random, pure, strict n-locus models with specified genetic constraints. These constraints include heritability, minor allele frequencies of the SNPs, and population prevalence. GAMETES also includes a simple dataset simulation strategy which may be utilized to rapidly generate an archive of simulated datasets for given genetic models. We highlight the utility and limitations of GAMETES with an example simulation study using MDR, an algorithm designed to detect epistasis. GAMETES is a fast, flexible, and precise tool for generating complex n-locus models with random architectures. While GAMETES has a limited ability to generate models with higher heritabilities, it is proficient at generating the lower heritability models typically used in simulation studies evaluating new algorithms. In addition, the GAMETES modeling strategy may be flexibly combined with any dataset simulation strategy. Beyond dataset simulation, GAMETES could be employed to pursue theoretical characterization of genetic models and epistasis.

Reference centiles for the middle cerebral artery and umbilical artery pulsatility index and cerebro-placental ratio from a low-risk population - a Generalised Additive Model for Location, Shape and Scale (GAMLSS) approach.

PubMed

Flatley, Christopher; Kumar, Sailesh; Greer, Ristan M

2018-02-06

The primary aim of this study was to create reference ranges for the fetal Middle Cerebral artery Pulsatility Index (MCA PI), Umbilical Artery Pulsatility Index (UA PI) and the Cerebro-Placental Ratio (CPR) in a clearly defined low-risk cohort using the Generalised Additive Model for Location, Shape and Scale (GAMLSS) method. Prospectively collected cross-sectional biometry and Doppler data from low-risk women attending the Mater Mother's Hospital, Maternal and Fetal Medicine Department in Brisbane, Australia between January 2010 and April 2017 were used to derive gestation specific centiles for the MCA PI, UA PI and CPR. All ultrasound scans were performed between 18 + 0 and 41 + 6 weeks gestation with recorded data for the MCA PI and/or UA PI. The GAMLSS method was used for the calculation of gestational age-adjusted centiles. Distributions and additive terms were assessed and the final model was chosen on the basis of the Global Deviance, Akaike information criterion (AIC) and Schwartz bayesian criterion (SBC), along with the results of the model and residual diagnostics as well as visual assessment of the centiles themselves. Over the study period 6013 women met the inclusion criteria. The MCA PI was recorded in 4473 fetuses, the UA PI in 6008 fetuses and the CPR was able to be calculated in 4464 cases. The centiles for the MCA PI used a fractional polynomial additive term and Box-Cox t (BCT) distribution. Centiles for the UA PI used a cubic spline additive term with BCT distribution and the CPR used a fractional polynomial additive term and a BCT distribution. We have created gestational centile reference ranges for the MCA PI, UA PI and CPR from a large low-risk cohort that supports their applicability and generalisability.

Optimal policies of non-cross-resistant chemotherapy on Goldie and Coldman's cancer model.

PubMed

Chen, Jeng-Huei; Kuo, Ya-Hui; Luh, Hsing Paul

2013-10-01

Mathematical models can be used to study the chemotherapy on tumor cells. Especially, in 1979, Goldie and Coldman proposed the first mathematical model to relate the drug sensitivity of tumors to their mutation rates. Many scientists have since referred to this pioneering work because of its simplicity and elegance. Its original idea has also been extended and further investigated in massive follow-up studies of cancer modeling and optimal treatment. Goldie and Coldman, together with Guaduskas, later used their model to explain why an alternating non-cross-resistant chemotherapy is optimal with a simulation approach. Subsequently in 1983, Goldie and Coldman proposed an extended stochastic based model and provided a rigorous mathematical proof to their earlier simulation work when the extended model is approximated by its quasi-approximation. However, Goldie and Coldman's analytic study of optimal treatments majorly focused on a process with symmetrical parameter settings, and presented few theoretical results for asymmetrical settings. In this paper, we recast and restate Goldie, Coldman, and Guaduskas' model as a multi-stage optimization problem. Under an asymmetrical assumption, the conditions under which a treatment policy can be optimal are derived. The proposed framework enables us to consider some optimal policies on the model analytically. In addition, Goldie, Coldman and Guaduskas' work with symmetrical settings can be treated as a special case of our framework. Based on the derived conditions, this study provides an alternative proof to Goldie and Coldman's work. In addition to the theoretical derivation, numerical results are included to justify the correctness of our work. Copyright © 2013 Elsevier Inc. All rights reserved.

Dynamic analysis of gas-core reactor system

NASA Technical Reports Server (NTRS)

Turner, K. H., Jr.

1973-01-01

A heat transfer analysis was incorporated into a previously developed model CODYN to obtain a model of open-cycle gaseous core reactor dynamics which can predict the heat flux at the cavity wall. The resulting model was used to study the sensitivity of the model to the value of the reactivity coefficients and to determine the system response for twenty specified perturbations. In addition, the model was used to study the effectiveness of several control systems in controlling the reactor. It was concluded that control drums located in the moderator region capable of inserting reactivity quickly provided the best control.

Impacts of half a degree additional warming on the Asian summer monsoon rainfall characteristics

NASA Astrophysics Data System (ADS)

Lee, Donghyun; Min, Seung-Ki; Fischer, Erich; Shiogama, Hideo; Bethke, Ingo; Lierhammer, Ludwig; Scinocca, John F.

2018-04-01

This study investigates the impacts of global warming of 1.5 °C and 2.0 °C above pre-industrial conditions (Paris Agreement target temperatures) on the South Asian and East Asian monsoon rainfall using five atmospheric global climate models participating in the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) project. Mean and extreme precipitation is projected to increase under warming over the two monsoon regions, more strongly in the 2.0 °C warmer world. Moisture budget analysis shows that increases in evaporation and atmospheric moisture lead to the additional increases in mean precipitation with good inter-model agreement. Analysis of daily precipitation characteristics reveals that more-extreme precipitation will have larger increase in intensity and frequency responding to the half a degree additional warming, which is more clearly seen over the South Asian monsoon region, indicating non-linear scaling of precipitation extremes with temperature. Strong inter-model relationship between temperature and precipitation intensity further demonstrates that the increased moisture with warming (Clausius-Clapeyron relation) plays a critical role in the stronger intensification of more-extreme rainfall with warming. Results from CMIP5 coupled global climate models under a transient warming scenario confirm that half a degree additional warming would bring more frequent and stronger heavy precipitation events, exerting devastating impacts on the human and natural system over the Asian monsoon region.

The potential application of European market research data in dietary exposure modelling of food additives.

PubMed

Tennant, David Robin; Bruyninckx, Chris

2018-03-01

Consumer exposure assessments for food additives are incomplete without information about the proportions of foods in each authorised category that contain the additive. Such information has been difficult to obtain but the Mintel Global New Products Database (GNPD) provides information about product launches across Europe over the past 20 years. These data can be searched to identify products with specific additives listed on product labels and the numbers compared with total product launches for food and drink categories in the same database to determine the frequency of occurrence. There are uncertainties associated with the data but these can be managed by adopting a cautious and conservative approach. GNPD data can be mapped with authorised food categories and with food descriptions used in the EFSA Comprehensive European Food Consumption Surveys Database for exposure modelling. The data, when presented as percent occurrence, could be incorporated into the EFSA ANS Panel's 'brand-loyal/non-brand loyal exposure model in a quantitative way. Case studies of preservative, antioxidant, colour and sweetener additives showed that the impact of including occurrence data is greatest in the non-brand loyal scenario. Recommendations for future research include identifying occurrence data for alcoholic beverages, linking regulatory food codes, FoodEx and GNPD product descriptions, developing the use of occurrence data for carry-over foods and improving understanding of brand loyalty in consumer exposure models.

Asymmetrical booster ascent guidance and control system design study. Volume 2: SSFS math models - Ascent. [space shuttle development

NASA Technical Reports Server (NTRS)

Williams, F. E.; Lemon, R. S.

1974-01-01

The engineering equations and mathematical models developed for use in the space shuttle functional simulator (SSFS) are presented, and include extensive revisions and additions to earlier documentation. Definitions of coordinate systems used by the SSFS models and coordinate tranformations are given, along with documentation of the flexible body mathematical models. The models were incorporated in the SSFS and are in the checkout stage.

Exposure to Violence and Parenting as Mediators between Poverty and Psychological Symptoms in Urban African American Adolescents

ERIC Educational Resources Information Center

Grant, K.E.; McCormick, A.; Poindexter, L.; Simpkins, T.; Janda, C.M.; Thomas, K.J.; Campbell, A.; Carleton, R.; Taylor, J.

2005-01-01

The present study builds on past research that has found support for a conceptual model in which poverty is linked with adolescent psychological symptoms through economic stressors and impaired parenting. The present study examined this model in a sample of urban African American mothers and their adolescent children. In addition, an alternative…

Undergraduate Student Retention in Context: An Examination of First-Year Risk Prediction and Advising Practices within a College of Education

ERIC Educational Resources Information Center

Litchfield, Bradley C.

2013-01-01

This study examined the use of an institutionally-specific risk prediction model in the university's College of Education. Set in a large, urban, public university, the risk model predicted incoming students' first-semester GPAs, which, in turn, predicted the students' risk of attrition. Additionally, the study investigated advising practices…

Developing Technical Expertise in Secondary Technical Schools: The Effect of 4C/ID Learning Environments

ERIC Educational Resources Information Center

Sarfo, Frederick K.; Elen, Jan

2007-01-01

In this study, the effectiveness of learning environments, developed in line with the specifications of the four components instructional design model (4C/ID model) and the additional effect of ICT for fostering the development of technical expertise in traditional Ghanaian classrooms, was assessed. The study had a one-by-one-by-two…

Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model.

PubMed

Tsamados, Michel; Feltham, Daniel; Petty, Alek; Schroeder, David; Flocco, Daniela

2015-10-13

We present a modelling study of processes controlling the summer melt of the Arctic sea ice cover. We perform a sensitivity study and focus our interest on the thermodynamics at the ice-atmosphere and ice-ocean interfaces. We use the Los Alamos community sea ice model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the ice-ocean interface; and (iii) a new lateral melt parametrization. Recent additions to the CICE model are also tested, including explicit melt ponds, a form drag parametrization and a halodynamic brine drainage scheme. The various sea ice parametrizations tested in this sensitivity study introduce a wide spread in the simulated sea ice characteristics. For each simulation, the total melt is decomposed into its surface, bottom and lateral melt components to assess the processes driving melt and how this varies regionally and temporally. Because this study quantifies the relative importance of several processes in driving the summer melt of sea ice, this work can serve as a guide for future research priorities. © 2015 The Author(s).

Evaluating the cost effectiveness of environmental projects: Case studies in aerospace and defense

NASA Technical Reports Server (NTRS)

Shunk, James F.

1995-01-01

Using the replacement technology of high pressure waterjet decoating systems as an example, a simple methodology is presented for developing a cost effectiveness model. The model uses a four-step process to formulate an economic justification designed for presentation to decision makers as an assessment of the value of the replacement technology over conventional methods. Three case studies from major U.S. and international airlines are used to illustrate the methodology and resulting model. Tax and depreciation impacts are also presented as potential additions to the model.

Large-scale Watershed Modeling: NHDPlus Resolution with Achievable Conservation Scenarios in the Western Lake Erie Basin

NASA Astrophysics Data System (ADS)

Yen, H.; White, M. J.; Arnold, J. G.; Keitzer, S. C.; Johnson, M. V. V.; Atwood, J. D.; Daggupati, P.; Herbert, M. E.; Sowa, S. P.; Ludsin, S.; Robertson, D. M.; Srinivasan, R.; Rewa, C. A.

2016-12-01

By the substantial improvement of computer technology, large-scale watershed modeling has become practically feasible in conducting detailed investigations of hydrologic, sediment, and nutrient processes. In the Western Lake Erie Basin (WLEB), water quality issues caused by anthropogenic activities are not just interesting research subjects but, have implications related to human health and welfare, as well as ecological integrity, resistance, and resilience. In this study, the Soil and Water Assessment Tool (SWAT) and the finest resolution stream network, NHDPlus, were implemented on the WLEB to examine the interactions between achievable conservation scenarios with corresponding additional projected costs. During the calibration/validation processes, both hard (temporal) and soft (non-temporal) data were used to ensure the modeling outputs are coherent with actual watershed behavior. The results showed that widespread adoption of conservation practices intended to provide erosion control could deliver average reductions of sediment and nutrients without additional nutrient management changes. On the other hand, responses of nitrate (NO3) and dissolved inorganic phosphorus (DIP) dynamics may be different than responses of total nitrogen and total phosphorus dynamics under the same conservation practice. Model results also implied that fewer financial resources are required to achieve conservation goals if the goal is to achieve reductions in targeted watershed outputs (ex. NO3 or DIP) rather than aggregated outputs (ex. total nitrogen or total phosphorus). In addition, it was found that the model's capacity to simulate seasonal effects and responses to changing conservation adoption on a seasonal basis could provide a useful index to help alleviate additional cost through temporal targeting of conservation practices. Scientists, engineers, and stakeholders can take advantage of the work performed in this study as essential information while conducting policy making processes in the future.

Cardiovascular risk assessment: addition of CKD and race to the Framingham equation

PubMed Central

Drawz, Paul E.; Baraniuk, Sarah; Davis, Barry R.; Brown, Clinton D.; Colon, Pedro J.; Cujyet, Aloysius B.; Dart, Richard A.; Graumlich, James F.; Henriquez, Mario A.; Moloo, Jamaluddin; Sakalayen, Mohammed G.; Simmons, Debra L.; Stanford, Carol; Sweeney, Mary Ellen; Wong, Nathan D.; Rahman, Mahboob

2012-01-01

Background/Aims The value of the Framingham equation in predicting cardiovascular risk in African Americans and patients with chronic kidney disease (CKD) is unclear. The purpose of the study was to evaluate whether the addition of CKD and race to the Framingham equation improves risk stratification in hypertensive patients. Methods Participants in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) were studied. Those randomized to doxazosin, age greater than 74 years, and those with a history of coronary heart disease (CHD) were excluded. Two risk stratification models were developed using Cox proportional hazards models in a two-thirds developmental sample. The first model included the traditional Framingham risk factors. The second model included the traditional risk factors plus CKD, defined by eGFR categories, and stratification by race (Black vs. Non-Black). The primary outcome was a composite of fatal CHD, nonfatal MI, coronary revascularization, and hospitalized angina. Results There were a total of 19,811 eligible subjects. In the validation cohort, there was no difference in C-statistics between the Framingham equation and the ALLHAT model including CKD and race. This was consistent across subgroups by race and gender and among those with CKD. One exception was among Non-Black women where the C-statistic was higher for the Framingham equation (0.68 vs 0.65, P=0.02). Additionally, net reclassification improvement was not significant for any subgroup based on race and gender, ranging from −5.5% to 4.4%. Conclusion The addition of CKD status and stratification by race does not improve risk prediction in high-risk hypertensive patients. PMID:23194494

Fertility decisions and desires in Bangladesh: an econometric investigation.

PubMed

Sirageldin, I; Khan, M A; Shah, F; Ariturk, A

1976-07-01

2 models are developed to examine fertility behavior in Bangladesh. The 1st model deals with the total number of ever-born children to a couple; the 2nd examines sequential decisions that characterize the desire for an additional child. The "Chicago-Columbia" or "New Home Economics" approach is used, but to the usual economic variables are added sociological and demographic variables; and fertility is examined in relation to the prices of child services consumed as well as a valuation of the mother's time. The data for the study were drawn from a sample of 3088 currently married women respondents to the 1968/69 Impact Survey (an extended KAP survey). The model for completed family size uses 4 endogenous variables: total live births, number of dead children, current income, and female labor force participation; these are examined in terms of 14 exogenous variables, including property ownership, age, literacy, awareness of family planning, rural vs urban, type of family, size of family, and schooling. The model is built on 4 equations with parameters estimated by 2-stage least squares technic and then subjected to multivariate analysis. The model for demand for additional children added 5 exogenous variables including sex of children, desire for children, and perceived need for education of children. This model was examined using standard probit analysis. Interpretation of the 2 models showed that 1) Income was positively related to completed family size but has no effect on desire for additional children; 2) female education, female employment, and cost of fertility control had no effect in either model; 3) Age at marriage had a positive effect on completed family size but none on desire for additional children; 4) Urban women had more live births, but rural women were more likely to want additional children; 5) Sex preference for boys is intense in Bangladesh. The study concludes that: 1) Economic well-being effects fertility; 2) The more adequate couples consider their income, the more likely they are to want more children; 3) Female education and employment have no effect on either completed family size or desire for more children; 4) There are no clear effects of family planning programs on either; and 5) desire for more children decreases as the number of children, particularly sons, increases.

Random regression analyses using B-spline functions to model growth of Nellore cattle.

PubMed

Boligon, A A; Mercadante, M E Z; Lôbo, R B; Baldi, F; Albuquerque, L G

2012-02-01

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Testing for departures from additivity in mixtures of perfluoroalkyl acids (PFAAs)

EPA Science Inventory

This study is a follow-up to a paper by Carr, et al. that determined a design structure to optimally test for departures from additivity in a fixed ratio mixture of four perfluoroalkyl acids (PFAAs) using an in vitro transiently-transfected COS- 1 PPARa reporter model with an NHA...

Firm performance model in small and medium enterprises (SMEs) based on learning orientation and innovation

NASA Astrophysics Data System (ADS)

Lestari, E. R.; Ardianti, F. L.; Rachmawati, L.

2018-03-01

This study investigated the relationship between learning orientation, innovation, and firm performance. A conceptual model and hypothesis were empirically examined using structural equation modelling. The study involved a questionnaire-based survey of owners of small and medium enterprises (SMEs) operating in Batu City, Indonesia. The results showed that both variables of learning orientation and innovation effect positively on firm performance. Additionally, learning orientation has positive effect innovation. This study has implication for SMEs aiming at increasing their firm performance based on learning orientation and innovation capability.

Additive Manufacturing (3D Printing) Aircraft Parts and Tooling at the Maintenance Group Level

DTIC Science & Technology

The purpose of this research was to evaluate the effectiveness of additive manufacturing (AM) or 3D printing for the Air Force aircraft maintenance...case study of the 552d MXGs 3D printing operation explores their use of a Fused Deposition Modeling (FDM) thermoplastic material to manufacture parts...by applying the case study’s analysis toward a proof of concept, producing a C-130J Aft Cargo Door Rub Strip for 3D printing . The study concluded by

A model-averaging method for assessing groundwater conceptual model uncertainty.

PubMed

Ye, Ming; Pohlmann, Karl F; Chapman, Jenny B; Pohll, Greg M; Reeves, Donald M

2010-01-01

This study evaluates alternative groundwater models with different recharge and geologic components at the northern Yucca Flat area of the Death Valley Regional Flow System (DVRFS), USA. Recharge over the DVRFS has been estimated using five methods, and five geological interpretations are available at the northern Yucca Flat area. Combining the recharge and geological components together with additional modeling components that represent other hydrogeological conditions yields a total of 25 groundwater flow models. As all the models are plausible given available data and information, evaluating model uncertainty becomes inevitable. On the other hand, hydraulic parameters (e.g., hydraulic conductivity) are uncertain in each model, giving rise to parametric uncertainty. Propagation of the uncertainty in the models and model parameters through groundwater modeling causes predictive uncertainty in model predictions (e.g., hydraulic head and flow). Parametric uncertainty within each model is assessed using Monte Carlo simulation, and model uncertainty is evaluated using the model averaging method. Two model-averaging techniques (on the basis of information criteria and GLUE) are discussed. This study shows that contribution of model uncertainty to predictive uncertainty is significantly larger than that of parametric uncertainty. For the recharge and geological components, uncertainty in the geological interpretations has more significant effect on model predictions than uncertainty in the recharge estimates. In addition, weighted residuals vary more for the different geological models than for different recharge models. Most of the calibrated observations are not important for discriminating between the alternative models, because their weighted residuals vary only slightly from one model to another.

Daily River Flow Forecasting with Hybrid Support Vector Machine – Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Zaini, N.; Malek, M. A.; Yusoff, M.; Mardi, N. H.; Norhisham, S.

2018-04-01

The application of artificial intelligence techniques for river flow forecasting can further improve the management of water resources and flood prevention. This study concerns the development of support vector machine (SVM) based model and its hybridization with particle swarm optimization (PSO) to forecast short term daily river flow at Upper Bertam Catchment located in Cameron Highland, Malaysia. Ten years duration of historical rainfall, antecedent river flow data and various meteorology parameters data from 2003 to 2012 are used in this study. Four SVM based models are proposed which are SVM1, SVM2, SVM-PSO1 and SVM-PSO2 to forecast 1 to 7 day ahead of river flow. SVM1 and SVM-PSO1 are the models with historical rainfall and antecedent river flow as its input, while SVM2 and SVM-PSO2 are the models with historical rainfall, antecedent river flow data and additional meteorological parameters as input. The performances of the proposed model are measured in term of RMSE and R2 . It is found that, SVM2 outperformed SVM1 and SVM-PSO2 outperformed SVM-PSO1 which meant the additional meteorology parameters used as input to the proposed models significantly affect the model performances. Hybrid models SVM-PSO1 and SVM-PSO2 yield higher performances as compared to SVM1 and SVM2. It is found that hybrid models are more effective in forecasting river flow at 1 to 7 day ahead at the study area.

A Study on the Application of the Information-Motivation-Behavioral Skills (IMB) Model on Rational Drug Use Behavior among Second-Level Hospital Outpatients in Anhui, China.

PubMed

Bian, Cheng; Xu, Shuman; Wang, Heng; Li, Niannian; Wu, Jingya; Zhao, Yunwu; Li, Peng; Lu, Hua

2015-01-01

The high prevalence of risky irrational drug use behaviors mean that outpatients face high risks of drug resistance and even death. This study represents the first application of the Information-Motivation-Behavioral Skills (IMB) model on rational drug use behavior among second-level hospital outpatients from three prefecture-level cities in Anhui, China. Using the IMB model, our study examined predictors of rational drug use behavior and determined the associations between the model constructs. This study was conducted with a sample of 1,214 outpatients aged 18 years and older in Anhui second-level hospitals and applied the structural equation model (SEM) to test predictive relations among the IMB model variables related to rational drug use behavior. Age, information and motivation had significant direct effects on rational drug use behavior. Behavioral skills as an intermediate variable also significantly predicted more rational drug use behavior. Female gender, higher educational level, more information and more motivation predicted more behavioral skills. In addition, there were significant indirect impacts on rational drug use behavior mediated through behavioral skills. The IMB-based model explained the relationships between the constructs and rational drug use behavior of outpatients in detail, and it suggests that future interventions among second-level hospital outpatients should consider demographic characteristics and should focus on improving motivation and behavioral skills in addition to the publicity of knowledge.

A Study on the Application of the Information-Motivation-Behavioral Skills (IMB) Model on Rational Drug Use Behavior among Second-Level Hospital Outpatients in Anhui, China

PubMed Central

Wang, Heng; Li, Niannian; Wu, Jingya; Zhao, Yunwu; Li, Peng; Lu, Hua

2015-01-01

Background The high prevalence of risky irrational drug use behaviors mean that outpatients face high risks of drug resistance and even death. This study represents the first application of the Information-Motivation-Behavioral Skills (IMB) model on rational drug use behavior among second-level hospital outpatients from three prefecture-level cities in Anhui, China. Using the IMB model, our study examined predictors of rational drug use behavior and determined the associations between the model constructs. Methods This study was conducted with a sample of 1,214 outpatients aged 18 years and older in Anhui second-level hospitals and applied the structural equation model (SEM) to test predictive relations among the IMB model variables related to rational drug use behavior. Results Age, information and motivation had significant direct effects on rational drug use behavior. Behavioral skills as an intermediate variable also significantly predicted more rational drug use behavior. Female gender, higher educational level, more information and more motivation predicted more behavioral skills. In addition, there were significant indirect impacts on rational drug use behavior mediated through behavioral skills. Conclusions The IMB-based model explained the relationships between the constructs and rational drug use behavior of outpatients in detail, and it suggests that future interventions among second-level hospital outpatients should consider demographic characteristics and should focus on improving motivation and behavioral skills in addition to the publicity of knowledge. PMID:26275301

Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

NASA Astrophysics Data System (ADS)

Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.

2018-02-01

The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental design study to test the effectiveness of a model-based curriculum focused on the concepts of natural selection and population ecology that makes use of Excel modeling tools (Modeling Instruction in Biology with Excel, MBI-E). The curriculum revolves around the bio-engineering practice of controlling an invasive species. The study takes place in the Midwest within ten high schools teaching a regular-level introductory biology class. A post-test was designed that targeted a number of common misconceptions in both concept areas as well as representational usage. The results of a post-test demonstrate that the MBI-E students significantly outperformed the traditional classes in both natural selection and population ecology concepts, thus overcoming a number of misconceptions. In addition, implementing students made use of more multiple representations as well as demonstrating greater fascination for science.

The partly Aalen's model for recurrent event data with a dependent terminal event.

PubMed

Chen, Chyong-Mei; Shen, Pao-Sheng; Chuang, Ya-Wen

2016-01-30

Recurrent event data are commonly observed in biomedical longitudinal studies. In many instances, there exists a terminal event, which precludes the occurrence of additional repeated events, and usually there is also a nonignorable correlation between the terminal event and recurrent events. In this article, we propose a partly Aalen's additive model with a multiplicative frailty for the rate function of recurrent event process and assume a Cox frailty model for terminal event time. A shared gamma frailty is used to describe the correlation between the two types of events. Consequently, this joint model can provide the information of temporal influence of absolute covariate effects on the rate of recurrent event process, which is usually helpful in the decision-making process for physicians. An estimating equation approach is developed to estimate marginal and association parameters in the joint model. The consistency of the proposed estimator is established. Simulation studies demonstrate that the proposed approach is appropriate for practical use. We apply the proposed method to a peritonitis cohort data set for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluation of MEDALUS model for desertification hazard zonation using GIS; study area: Iyzad Khast plain, Iran.

PubMed

Farajzadeh, Manuchehr; Egbal, Mahbobeh Nik

2007-08-15

In this study, the MEDALUS model along with GIS mapping techniques are used to determine desertification hazards for a province of Iran to determine the desertification hazard. After creating a desertification database including 20 parameters, the first steps consisted of developing maps of four indices for the MEDALUS model including climate, soil, vegetation and land use were prepared. Since these parameters have mostly been presented for the Mediterranean region in the past, the next step included the addition of other indicators such as ground water and wind erosion. Then all of the layers weighted by environmental conditions present in the area were used (following the same MEDALUS framework) before a desertification map was prepared. The comparison of two maps based on the original and modified MEDALUS models indicates that the addition of more regionally-specific parameters into the model allows for a more accurate representation of desertification processes across the Iyzad Khast plain. The major factors affecting desertification in the area are climate, wind erosion and low land quality management, vegetation degradation and the salinization of soil and water resources.

Estimating urban ground-level PM10 using MODIS 3km AOD product and meteorological parameters from WRF model

NASA Astrophysics Data System (ADS)

Ghotbi, Saba; Sotoudeheian, Saeed; Arhami, Mohammad

2016-09-01

Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable urban area, Tehran, Iran. Despite the critical particulate pollution problem, very few PM studies were conducted in this area. The issue of rather poor direct PM-AOD associations existed, due to different factors such as variations in particles optical properties, in addition to bright background issue for satellite data, as the studied area located in the semi-arid areas of Middle East. Statistical approach of linear mixed effect (LME) was used, and three types of statistical models including single variable LME model (using AOD as independent variable) and multiple variables LME model by using meteorological data from two sources, WRF model and synoptic stations, were examined. Meteorological simulations were performed using a multiscale approach and creating an appropriate physic for the studied region, and the results showed rather good agreements with recordings of the synoptic stations. The single variable LME model was able to explain about 61%-73% of daily PM10 variations, reflecting a rather acceptable performance. Statistical models performance improved through using multivariable LME and incorporating meteorological data as auxiliary variables, particularly by using fine resolution outputs from WRF (R2 = 0.73-0.81). In addition, rather fine resolution for PM estimates was mapped for the studied city, and resulting concentration maps were consistent with PM recordings at the existing stations.

Integrating Nonadditive Genomic Relationship Matrices into the Study of Genetic Architecture of Complex Traits.

PubMed

Nazarian, Alireza; Gezan, Salvador A

2016-03-01

The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dual effects of phloretin and phloridzin on the glycation induced by methylglyoxal in model systems.

PubMed

Ma, Jinyu; Peng, Xiaofang; Zhang, Xinchen; Chen, Feng; Wang, Mingfu

2011-08-15

In the present study, the dual effects of phloretin and phloridzin on methylglyoxal (MGO)-induced glycation were investigated in three N(α)-acetyl amino acid (arginine, cysteine, and lysine) models and three N-terminal polypeptide (PP01, PP02, and PP03 containing arginine, cysteine, and lysine, respectively) models. In both N(α)-acetyl amino acids and N-terminal polypeptides models, the arginine residue was confirmed as the major target for modification induced by MGO. Meanwhile, MGO modification was significantly inhibited by the addition of phloretin or phloridzin via their MGO-trapping abilities, with phloretin being more effective. Interestingly, the cysteine residue was intact when solely incubated with MGO, whereas the consumption of N(α)-acetylcysteine and PP02 was promoted by the addition of phloretin. Additional adducts, [N(α)-acetylcysteine + 2MGO + phloretin-H(2)O] and [2N(α)-acetylcysteine + 2MGO + phloretin-2H(2)O] were formed in the model composed of N(α)-acetylcysteine, MGO, and phloretin. Another adduct, [PP02 + 2MGO + phloretin-H(2)O] was observed in the model composed of PP02, MGO, and phloretin. The generation of adducts indicates that phloretin could directly participate in the modification of the cysteine residue in the presence of MGO. When creatine kinase (model protein) was exposed to MGO, the addition of phloridzin did not show a significant effect on retaining the activity of creatine kinase impaired by MGO, whereas the addition of phloretin completely inactivated creatine kinase. Results of the mass spectrometric analysis of intact creatine kinase in different models demonstrated that phloretin could directly participate in the reaction between creatine kinase and MGO, which would lead to the inactivation of creatine kinase. Furthermore, the addition of N(α)-acetylcysteine was found to maintain the activity of creatine kinase incubated with phloretin and MGO. These results showed that phloretin and phloridzin could inhibit the modification of the arginine residue by MGO and that phloretin could directly participate in the reaction between the thiol group and MGO.

Accounting for nonsampling error in estimates of HIV epidemic trends from antenatal clinic sentinel surveillance

PubMed Central

Eaton, Jeffrey W.; Bao, Le

2017-01-01

Objectives The aim of the study was to propose and demonstrate an approach to allow additional nonsampling uncertainty about HIV prevalence measured at antenatal clinic sentinel surveillance (ANC-SS) in model-based inferences about trends in HIV incidence and prevalence. Design Mathematical model fitted to surveillance data with Bayesian inference. Methods We introduce a variance inflation parameter σinfl2 that accounts for the uncertainty of nonsampling errors in ANC-SS prevalence. It is additive to the sampling error variance. Three approaches are tested for estimating σinfl2 using ANC-SS and household survey data from 40 subnational regions in nine countries in sub-Saharan, as defined in UNAIDS 2016 estimates. Methods were compared using in-sample fit and out-of-sample prediction of ANC-SS data, fit to household survey prevalence data, and the computational implications. Results Introducing the additional variance parameter σinfl2 increased the error variance around ANC-SS prevalence observations by a median of 2.7 times (interquartile range 1.9–3.8). Using only sampling error in ANC-SS prevalence ( σinfl2=0), coverage of 95% prediction intervals was 69% in out-of-sample prediction tests. This increased to 90% after introducing the additional variance parameter σinfl2. The revised probabilistic model improved model fit to household survey prevalence and increased epidemic uncertainty intervals most during the early epidemic period before 2005. Estimating σinfl2 did not increase the computational cost of model fitting. Conclusions: We recommend estimating nonsampling error in ANC-SS as an additional parameter in Bayesian inference using the Estimation and Projection Package model. This approach may prove useful for incorporating other data sources such as routine prevalence from Prevention of mother-to-child transmission testing into future epidemic estimates. PMID:28296801

Soil Quality Index Determination Models for Restinga Forest

NASA Astrophysics Data System (ADS)

Bonilha, R. M.; Casagrande, J. C.; Soares, R. M.

2012-04-01

The Restinga Forest is a set of plant communities in mosaic, determined by the characteristics of their substrates as a result of depositional processes and ages. In this complex mosaic are the physiognomies of restinga forests of high-stage regeneration (high restinga) and middle stage of regeneration (low restinga), each with its plant characteristics that differentiate them. Located on the coastal plains of the Brazilian coast, suffering internal influences both the continental slopes, as well as from the sea. Its soils come from the Quaternary and are subject to constant deposition of sediments. The climate in the coastal type is tropical (Köppen). This work was conducted in four locations: (1) Anchieta Island, Ubatuba, (2) Juréia-Itatins Ecological Station, Iguape, (3) Vila das Pedrinhas, Comprida Island; and (4) Cardoso Island, Cananeia. The soil samples were collect at a depths of 0 to 5, 0-10, 0-20, 20-40 and 40 to 60cm for the chemical and physical analysis. Were studied the additive and pondering additive models to evaluate soil quality. It was concluded: a) the comparative additive model produces quantitative results and the pondering additive model quantitative results; b) as the pondering additive model, the values of Soil Quality Index (SQI) for soils under forest of restinga are low and realistic, demonstrating the small plant biomass production potential of these soils, as well as their low resilience; c) the values of SQI similar to areas with and without restinga forest give quantitative demonstration of the restinga be considered as soil phase; d) restinga forest, probably, is maintained solely by the cycling of nutrients in a closed nutrient cycling; e) for the determination of IQS for soils under restinga vegetation the use of routine chemical analysis is adequate. Keywords: Model, restinga forest, Soil Quality Index (SQI).

Classification techniques on computerized systems to predict and/or to detect Apnea: A systematic review.

PubMed

Pombo, Nuno; Garcia, Nuno; Bousson, Kouamana

2017-03-01

Sleep apnea syndrome (SAS), which can significantly decrease the quality of life is associated with a major risk factor of health implications such as increased cardiovascular disease, sudden death, depression, irritability, hypertension, and learning difficulties. Thus, it is relevant and timely to present a systematic review describing significant applications in the framework of computational intelligence-based SAS, including its performance, beneficial and challenging effects, and modeling for the decision-making on multiple scenarios. This study aims to systematically review the literature on systems for the detection and/or prediction of apnea events using a classification model. Forty-five included studies revealed a combination of classification techniques for the diagnosis of apnea, such as threshold-based (14.75%) and machine learning (ML) models (85.25%). In addition, the ML models, were clustered in a mind map, include neural networks (44.26%), regression (4.91%), instance-based (11.47%), Bayesian algorithms (1.63%), reinforcement learning (4.91%), dimensionality reduction (8.19%), ensemble learning (6.55%), and decision trees (3.27%). A classification model should provide an auto-adaptive and no external-human action dependency. In addition, the accuracy of the classification models is related with the effective features selection. New high-quality studies based on randomized controlled trials and validation of models using a large and multiple sample of data are recommended. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios

NASA Astrophysics Data System (ADS)

Goderniaux, Pascal; BrouyèRe, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley J.; Orban, Philippe; Dassargues, Alain

2011-12-01

Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software "HydroGeoSphere." This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China.

PubMed

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China

PubMed Central

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia. PMID:27002822

A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models

PubMed Central

Rolls, David A.; Wang, Peng; McBryde, Emma; Pattison, Philippa; Robins, Garry

2015-01-01

We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a “hidden population”. In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure. PMID:26555701

Cost-Effectiveness of HBV and HCV Screening Strategies – A Systematic Review of Existing Modelling Techniques

PubMed Central

Geue, Claudia; Wu, Olivia; Xin, Yiqiao; Heggie, Robert; Hutchinson, Sharon; Martin, Natasha K.; Fenwick, Elisabeth; Goldberg, David

2015-01-01

Introduction Studies evaluating the cost-effectiveness of screening for Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) are generally heterogeneous in terms of risk groups, settings, screening intervention, outcomes and the economic modelling framework. It is therefore difficult to compare cost-effectiveness results between studies. This systematic review aims to summarise and critically assess existing economic models for HBV and HCV in order to identify the main methodological differences in modelling approaches. Methods A structured search strategy was developed and a systematic review carried out. A critical assessment of the decision-analytic models was carried out according to the guidelines and framework developed for assessment of decision-analytic models in Health Technology Assessment of health care interventions. Results The overall approach to analysing the cost-effectiveness of screening strategies was found to be broadly consistent for HBV and HCV. However, modelling parameters and related structure differed between models, producing different results. More recent publications performed better against a performance matrix, evaluating model components and methodology. Conclusion When assessing screening strategies for HBV and HCV infection, the focus should be on more recent studies, which applied the latest treatment regimes, test methods and had better and more complete data on which to base their models. In addition to parameter selection and associated assumptions, careful consideration of dynamic versus static modelling is recommended. Future research may want to focus on these methodological issues. In addition, the ability to evaluate screening strategies for multiple infectious diseases, (HCV and HIV at the same time) might prove important for decision makers. PMID:26689908

Empirical validation of landscape resistance models: insights from the Greater Sage-Grouse (Centrocercus urophasianus)

Treesearch

Andrew J. Shirk; Michael A. Schroeder; Leslie A. Robb; Samuel A. Cushman

2015-01-01

The ability of landscapes to impede species’ movement or gene flow may be quantified by resistance models. Few studies have assessed the performance of resistance models parameterized by expert opinion. In addition, resistance models differ in terms of spatial and thematic resolution as well as their focus on the ecology of a particular species or more generally on the...

Antenatal blood pressure for prediction of pre-eclampsia, preterm birth, and small for gestational age babies: development and validation in two general population cohorts

PubMed Central

Silverwood, Richard J; de Stavola, Bianca L; Inskip, Hazel; Cooper, Cyrus; Godfrey, Keith M; Crozier, Sarah; Fraser, Abigail; Nelson, Scott M; Lawlor, Debbie A; Tilling, Kate

2015-01-01

Study question Can routine antenatal blood pressure measurements between 20 and 36 weeks’ gestation contribute to the prediction of pre-eclampsia and its associated adverse outcomes? Methods This study used repeated antenatal measurements of blood pressure from 12 996 women in the Avon Longitudinal Study of Parents and Children (ALSPAC) to develop prediction models and validated these in 3005 women from the Southampton Women’s Survey (SWS). A model based on maternal early pregnancy characteristics only (BMI, height, age, parity, smoking, existing and previous gestational hypertension and diabetes, and ethnicity) plus initial mean arterial pressure was compared with a model additionally including current mean arterial pressure, a model including the deviation of current mean arterial pressure from a stratified normogram, and a model including both at different gestational ages from 20-36 weeks. Study answer and limitations The addition of blood pressure measurements from 28 weeks onwards improved prediction models compared with use of early pregnancy risk factors alone, but they contributed little to the prediction of preterm birth or small for gestational age. Though multiple imputation of missing data was used to increase the sample size and minimise selection bias, the validation sample might have been slightly underpowered as the number of cases of pre-eclampsia was just below the recommended 100. Several risk factors were self reported, potentially introducing measurement error, but this reflects how information would be obtained in clinical practice. What this study adds The addition of routinely collected blood pressure measurements from 28 weeks onwards improves predictive models for pre-eclampsia based on blood pressure in early pregnancy and other characteristics, facilitating a reduction in scheduled antenatal care. Funding, competing interests, data sharing UK Wellcome Trust, US National Institutes of Health, and UK Medical Research Council. Other funding sources for authors are detailed in the full online paper. With the exceptions of CM-W, HMI, and KMG there were no competing interests. PMID:26578347

Analysis of a kinetic multi-segment foot model. Part I: Model repeatability and kinematic validity.

PubMed

Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L

2012-04-01

Kinematic multi-segment foot models are still evolving, but have seen increased use in clinical and research settings. The addition of kinetics may increase knowledge of foot and ankle function as well as influence multi-segment foot model evolution; however, previous kinetic models are too complex for clinical use. In this study we present a three-segment kinetic foot model and thorough evaluation of model performance during normal gait. In this first of two companion papers, model reference frames and joint centers are analyzed for repeatability, joint translations are measured, segment rigidity characterized, and sample joint angles presented. Within-tester and between-tester repeatability were first assessed using 10 healthy pediatric participants, while kinematic parameters were subsequently measured on 17 additional healthy pediatric participants. Repeatability errors were generally low for all sagittal plane measures as well as transverse plane Hindfoot and Forefoot segments (median<3°), while the least repeatable orientations were the Hindfoot coronal plane and Hallux transverse plane. Joint translations were generally less than 2mm in any one direction, while segment rigidity analysis suggested rigid body behavior for the Shank and Hindfoot, with the Forefoot violating the rigid body assumptions in terminal stance/pre-swing. Joint excursions were consistent with previously published studies. Copyright © 2012 Elsevier B.V. All rights reserved.

Modelling Nitrogen Oxides in Los Angeles Using a Hybrid Dispersion/Land Use Regression Model

NASA Astrophysics Data System (ADS)

Wilton, Darren C.

The goal of this dissertation is to develop models capable of predicting long term annual average NOx concentrations in urban areas. Predictions from simple meteorological dispersion models and seasonal proxies for NO2 oxidation were included as covariates in a land use regression (LUR) model for NOx in Los Angeles, CA. The NO x measurements were obtained from a comprehensive measurement campaign that is part of the Multi-Ethnic Study of Atherosclerosis Air Pollution Study (MESA Air). Simple land use regression models were initially developed using a suite of GIS-derived land use variables developed from various buffer sizes (R²=0.15). Caline3, a simple steady-state Gaussian line source model, was initially incorporated into the land-use regression framework. The addition of this spatio-temporally varying Caline3 covariate improved the simple LUR model predictions. The extent of improvement was much more pronounced for models based solely on the summer measurements (simple LUR: R²=0.45; Caline3/LUR: R²=0.70), than it was for models based on all seasons (R²=0.20). We then used a Lagrangian dispersion model to convert static land use covariates for population density, commercial/industrial area into spatially and temporally varying covariates. The inclusion of these covariates resulted in significant improvement in model prediction (R²=0.57). In addition to the dispersion model covariates described above, a two-week average value of daily peak-hour ozone was included as a surrogate of the oxidation of NO2 during the different sampling periods. This additional covariate further improved overall model performance for all models. The best model by 10-fold cross validation (R²=0.73) contained the Caline3 prediction, a static covariate for length of A3 roads within 50 meters, the Calpuff-adjusted covariates derived from both population density and industrial/commercial land area, and the ozone covariate. This model was tested against annual average NOx concentrations from an independent data set from the EPA's Air Quality System (AQS) and MESA Air fixed site monitors, and performed very well (R²=0.82).

Detonation product EOS studies: Using ISLS to refine CHEETAH

NASA Astrophysics Data System (ADS)

Zaug, Joseph; Fried, Larry; Hansen, Donald

2001-06-01

Knowledge of an effective interatomic potential function underlies any effort to predict or rationalize the properties of solids and liquids. The experiments we undertake are directed towards determination of equilibrium and dynamic properties of simple fluids at densities sufficiently high that traditional computational methods and semi-empirical forms successful at ambient conditions may require reconsideration. In this paper we present high-pressure and temperature experimental sound speed data on a suite of non-ideal simple fluids and fluid mixtures. Impulsive Stimulated Light Scattering conducted in the diamond-anvil cell offers an experimental approach to determine cross-pair potential interactions through equation of state determinations. In addition the kinetics of structural relaxation in fluids can be studied. We compare our experimental results with our thermochemical computational model CHEETAH. Computational models are systematically improved with each addition of experimental data. Experimentally grounded computational models provide a good basis to confidently understand the chemical nature of reactions at extreme conditions.

Reduction of carcinogenic 4(5)-methylimidazole in a caramel model system: influence of food additives.

PubMed

Seo, Seulgi; Ka, Mi-Hyun; Lee, Kwang-Geun

2014-07-09

The effect of various food additives on the formation of carcinogenic 4(5)-methylimidazole (4-MI) in a caramel model system was investigated. The relationship between the levels of 4-MI and various pyrazines was studied. When glucose and ammonium hydroxide were heated, the amount of 4-MI was 556 ± 1.3 μg/mL, which increased to 583 ± 2.6 μg/mL by the addition of 0.1 M of sodium sulfite. When various food additives, such as 0.1 M of iron sulfate, magnesium sulfate, zinc sulfate, tryptophan, and cysteine were added, the amount of 4-MI was reduced to 110 ± 0.7, 483 ± 2.0, 460 ± 2.0, 409 ± 4.4, and 397 ± 1.7 μg/mL, respectively. The greatest reduction, 80%, occurred with the addition of iron sulfate. Among the 12 pyrazines, 2-ethyl-6-methylpyrazine with 4-MI showed the highest correlation (r = -0.8239).

Ambient temperature and coronary heart disease mortality in Beijing, China: a time series study

PubMed Central

2012-01-01

Background Many studies have examined the association between ambient temperature and mortality. However, less evidence is available on the temperature effects on coronary heart disease (CHD) mortality, especially in China. In this study, we examined the relationship between ambient temperature and CHD mortality in Beijing, China during 2000 to 2011. In addition, we compared time series and time-stratified case-crossover models for the non-linear effects of temperature. Methods We examined the effects of temperature on CHD mortality using both time series and time-stratified case-crossover models. We also assessed the effects of temperature on CHD mortality by subgroups: gender (female and male) and age (age > =65 and age < 65). We used a distributed lag non-linear model to examine the non-linear effects of temperature on CHD mortality up to 15 lag days. We used Akaike information criterion to assess the model fit for the two designs. Results The time series models had a better model fit than time-stratified case-crossover models. Both designs showed that the relationships between temperature and group-specific CHD mortality were non-linear. Extreme cold and hot temperatures significantly increased the risk of CHD mortality. Hot effects were acute and short-term, while cold effects were delayed by two days and lasted for five days. The old people and women were more sensitive to extreme cold and hot temperatures than young and men. Conclusions This study suggests that time series models performed better than time-stratified case-crossover models according to the model fit, even though they produced similar non-linear effects of temperature on CHD mortality. In addition, our findings indicate that extreme cold and hot temperatures increase the risk of CHD mortality in Beijing, China, particularly for women and old people. PMID:22909034

Association between polymorphisms of estrogen receptor 2 and benign prostatic hyperplasia

PubMed Central

KIM, SU KANG; CHUNG, JOO-HO; PARK, HYUN CHUL; KIM, JUN HO; ANN, JAE HONG; PARK, HUN KUK; LEE, SANG HYUP; YOO, KOO HAN; LEE, BYUNG-CHEOL; KIM, YOUNG OCK

2015-01-01

Estrogens and estrogen receptors (ESRs) have been implicated in the stimulation of aberrant prostate growth and the development of prostate diseases. The aim of the present study was to investigate four single nucleotide polymorphisms (SNPs) of the ESR2 gene in order to examine whether ESR2 is a susceptibility gene for benign prostatic hyperplasia (BPH). In order to evaluate whether an association exists between ESR2 and BPH risk, four polymorphisms [rs4986938 (intron), rs17766755 (intron), rs12435857 (intron) and rs1256049 (Val328Val)] of the ESR2 gene were genotyped by direct sequencing. A total of 94 patients with BPH and 79 control subjects were examined. SNPStats and Haploview version 4.2 we used for the genetic analysis. Multiple logistic regression models (codominant1, codominant2, dominant, recessive and log-additive) were produced in order to obtain the odds ratio, 95% confidence interval and P-value. Three SNPs (rs4986938, rs17766755 and rs12435857) showed significant associations with BPH (rs4986938, P=0.015 in log-additive model; rs17766755, P=0.033 in codominant1 model, P=0.019 in dominant model and P=0.020 in log-additive model; rs12435857, P=0.023 in dominant model and P=0.011 in log-additive model). The minor alleles of these SNPs increased the risk of BPH, and the AAC haplotype showed significant association with BPH (χ2=6.34, P=0.0118). These data suggest that the ESR2 gene may be associated with susceptibility to BPH. PMID:26640585

Association between polymorphisms of estrogen receptor 2 and benign prostatic hyperplasia.

PubMed

Kim, Su Kang; Chung, Joo-Ho; Park, Hyun Chul; Kim, Jun Ho; Ann, Jae Hong; Park, Hun Kuk; Lee, Sang Hyup; Yoo, Koo Han; Lee, Byung-Cheol; Kim, Young Ock

2015-11-01

Estrogens and estrogen receptors (ESRs) have been implicated in the stimulation of aberrant prostate growth and the development of prostate diseases. The aim of the present study was to investigate four single nucleotide polymorphisms (SNPs) of the ESR2 gene in order to examine whether ESR2 is a susceptibility gene for benign prostatic hyperplasia (BPH). In order to evaluate whether an association exists between ESR2 and BPH risk, four polymorphisms [rs4986938 (intron), rs17766755 (intron), rs12435857 (intron) and rs1256049 (Val328Val)] of the ESR2 gene were genotyped by direct sequencing. A total of 94 patients with BPH and 79 control subjects were examined. SNPStats and Haploview version 4.2 we used for the genetic analysis. Multiple logistic regression models (codominant1, codominant2, dominant, recessive and log-additive) were produced in order to obtain the odds ratio, 95% confidence interval and P-value. Three SNPs (rs4986938, rs17766755 and rs12435857) showed significant associations with BPH (rs4986938, P=0.015 in log-additive model; rs17766755, P=0.033 in codominant1 model, P=0.019 in dominant model and P=0.020 in log-additive model; rs12435857, P=0.023 in dominant model and P=0.011 in log-additive model). The minor alleles of these SNPs increased the risk of BPH, and the AAC haplotype showed significant association with BPH (χ 2 =6.34, P=0.0118). These data suggest that the ESR2 gene may be associated with susceptibility to BPH.

Sensitivity Analysis of Median Lifetime on Radiation Risks Estimates for Cancer and Circulatory Disease amongst Never-Smokers

NASA Technical Reports Server (NTRS)

Chappell, Lori J.; Cucinotta, Francis A.

2011-01-01

Radiation risks are estimated in a competing risk formalism where age or time after exposure estimates of increased risks for cancer and circulatory diseases are folded with a probability to survive to a given age. The survival function, also called the life-table, changes with calendar year, gender, smoking status and other demographic variables. An outstanding problem in risk estimation is the method of risk transfer between exposed populations and a second population where risks are to be estimated. Approaches used to transfer risks are based on: 1) Multiplicative risk transfer models -proportional to background disease rates. 2) Additive risk transfer model -risks independent of background rates. In addition, a Mixture model is often considered where the multiplicative and additive transfer assumptions are given weighted contributions. We studied the influence of the survival probability on the risk of exposure induced cancer and circulatory disease morbidity and mortality in the Multiplicative transfer model and the Mixture model. Risks for never-smokers (NS) compared to the average U.S. population are estimated to be reduced between 30% and 60% dependent on model assumptions. Lung cancer is the major contributor to the reduction for NS, with additional contributions from circulatory diseases and cancers of the stomach, liver, bladder, oral cavity, esophagus, colon, a portion of the solid cancer remainder, and leukemia. Greater improvements in risk estimates for NS s are possible, and would be dependent on improved understanding of risk transfer models, and elucidating the role of space radiation on the various stages of disease formation (e.g. initiation, promotion, and progression).

The impact of manual threshold selection in medical additive manufacturing.

PubMed

van Eijnatten, Maureen; Koivisto, Juha; Karhu, Kalle; Forouzanfar, Tymour; Wolff, Jan

2017-04-01

Medical additive manufacturing requires standard tessellation language (STL) models. Such models are commonly derived from computed tomography (CT) images using thresholding. Threshold selection can be performed manually or automatically. The aim of this study was to assess the impact of manual and default threshold selection on the reliability and accuracy of skull STL models using different CT technologies. One female and one male human cadaver head were imaged using multi-detector row CT, dual-energy CT, and two cone-beam CT scanners. Four medical engineers manually thresholded the bony structures on all CT images. The lowest and highest selected mean threshold values and the default threshold value were used to generate skull STL models. Geometric variations between all manually thresholded STL models were calculated. Furthermore, in order to calculate the accuracy of the manually and default thresholded STL models, all STL models were superimposed on an optical scan of the dry female and male skulls ("gold standard"). The intra- and inter-observer variability of the manual threshold selection was good (intra-class correlation coefficients >0.9). All engineers selected grey values closer to soft tissue to compensate for bone voids. Geometric variations between the manually thresholded STL models were 0.13 mm (multi-detector row CT), 0.59 mm (dual-energy CT), and 0.55 mm (cone-beam CT). All STL models demonstrated inaccuracies ranging from -0.8 to +1.1 mm (multi-detector row CT), -0.7 to +2.0 mm (dual-energy CT), and -2.3 to +4.8 mm (cone-beam CT). This study demonstrates that manual threshold selection results in better STL models than default thresholding. The use of dual-energy CT and cone-beam CT technology in its present form does not deliver reliable or accurate STL models for medical additive manufacturing. New approaches are required that are based on pattern recognition and machine learning algorithms.

Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

PubMed Central

Colins, Andrea; Gerdtzen, Ziomara P.; Nuñez, Marco T.; Salgado, J. Cristian

2017-01-01

Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex systems. PMID:28072870

An extended supersonic combustion model for the dynamic analysis of hypersonic vehicles

NASA Technical Reports Server (NTRS)

Bossard, J. A.; Peck, R. E.; Schmidt, D. K.

1993-01-01

The development of an advanced dynamic model for aeroelastic hypersonic vehicles powered by air breathing engines requires an adequate engine model. This report provides a discussion of some of the more important features of supersonic combustion and their relevance to the analysis and design of supersonic ramjet engines. Of particular interest are those aspects of combustion that impact the control of the process. Furthermore, the report summarizes efforts to enhance the aeropropulsive/aeroelastic dynamic model developed at the Aerospace Research Center of Arizona State University by focusing on combustion and improved modeling of this flow. The expanded supersonic combustor model described here has the capability to model the effects of friction, area change, and mass addition, in addition to the heat addition process. A comparison is made of the results from four cases: (1) heat addition only; (2) heat addition plus friction; (3) heat addition, friction, and area reduction, and (4) heat addition, friction, area reduction, and mass addition. The relative impact of these effects on the Mach number, static temperature, and static pressure distributions within the combustor are then shown. Finally, the effects of frozen versus equilibrium flow conditions within the exhaust plume is discussed.

Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry.

PubMed

Palmer, Rohan H C; McGeary, John E; Heath, Andrew C; Keller, Matthew C; Brick, Leslie A; Knopik, Valerie S

2015-12-01

Genetic studies of alcohol dependence (AD) have identified several candidate loci and genes, but most observed effects are small and difficult to reproduce. A plausible explanation for inconsistent findings may be a violation of the assumption that genetic factors contributing to each of the seven DSM-IV criteria point to a single underlying dimension of risk. Given that recent twin studies suggest that the genetic architecture of AD is complex and probably involves multiple discrete genetic factors, the current study employed common single nucleotide polymorphisms in two multivariate genetic models to examine the assumption that the genetic risk underlying DSM-IV AD is unitary. AD symptoms and genome-wide single nucleotide polymorphism (SNP) data from 2596 individuals of European descent from the Study of Addiction: Genetics and Environment were analyzed using genomic-relatedness-matrix restricted maximum likelihood. DSM-IV AD symptom covariance was described using two multivariate genetic factor models. Common SNPs explained 30% (standard error=0.136, P=0.012) of the variance in AD diagnosis. Additive genetic effects varied across AD symptoms. The common pathway model approach suggested that symptoms could be described by a single latent variable that had a SNP heritability of 31% (0.130, P=0.008). Similarly, the exploratory genetic factor model approach suggested that the genetic variance/covariance across symptoms could be represented by a single genetic factor that accounted for at least 60% of the genetic variance in any one symptom. Additive genetic effects on DSM-IV alcohol dependence criteria overlap. The assumption of common genetic effects across alcohol dependence symptoms appears to be a valid assumption. © 2015 Society for the Study of Addiction.

Cross-Cultural Validation of the Preventive Health Model for Colorectal Cancer Screening: An Australian Study

ERIC Educational Resources Information Center

Flight, Ingrid H.; Wilson, Carlene J.; McGillivray, Jane; Myers, Ronald E.

2010-01-01

We investigated whether the five-factor structure of the Preventive Health Model for colorectal cancer screening, developed in the United States, has validity in Australia. We also tested extending the model with the addition of the factor Self-Efficacy to Screen using Fecal Occult Blood Test (SESFOBT). Randomly selected men and women aged between…

The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim

2016-01-01

The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest…

The Longitudinal Stability and Dynamics of Group Membership in the Dual-Factor Model of Mental Health: Psychosocial Predictors of Mental Health

ERIC Educational Resources Information Center

Kelly, Ryan M.; Hills, Kimberly J.; Huebner, E. Scott; McQuillin, Samuel D.

2012-01-01

This study examined the longitudinal stability and dynamics of group membership within the Greenspoon and Sakflofske's dual-factor model of mental health. This expanded model incorporates information about subjective well-being (SWB), in addition to psychopathological symptoms, to better identify the mental health status and current functioning of…

A 1D-2D coupled SPH-SWE model applied to open channel flow simulations in complicated geometries

NASA Astrophysics Data System (ADS)

Chang, Kao-Hua; Sheu, Tony Wen-Hann; Chang, Tsang-Jung

2018-05-01

In this study, a one- and two-dimensional (1D-2D) coupled model is developed to solve the shallow water equations (SWEs). The solutions are obtained using a Lagrangian meshless method called smoothed particle hydrodynamics (SPH) to simulate shallow water flows in converging, diverging and curved channels. A buffer zone is introduced to exchange information between the 1D and 2D SPH-SWE models. Interpolated water discharge values and water surface levels at the internal boundaries are prescribed as the inflow/outflow boundary conditions in the two SPH-SWE models. In addition, instead of using the SPH summation operator, we directly solve the continuity equation by introducing a diffusive term to suppress oscillations in the predicted water depth. The performance of the two approaches in calculating the water depth is comprehensively compared through a case study of a straight channel. Additionally, three benchmark cases involving converging, diverging and curved channels are adopted to demonstrate the ability of the proposed 1D and 2D coupled SPH-SWE model through comparisons with measured data and predicted mesh-based numerical results. The proposed model provides satisfactory accuracy and guaranteed convergence.

Development of an Unstructured, Three-Dimensional Material Response Design Tool

NASA Technical Reports Server (NTRS)

Schulz, Joseph; Stern, Eric; Palmer, Grant; Muppidi, Suman; Schroeder, Olivia

2017-01-01

A preliminary verification and validation of a new material response model is presented. This model, Icarus, is intended to serve as a design tool for the thermal protection systems of re-entry vehicles. Currently, the capability of the model is limited to simulating the pyrolysis of a material as a result of the radiative and convective surface heating imposed on the material from the surrounding high enthalpy gas. Since the major focus behind the development of Icarus has been model extensibility, the hope is that additional physics can be quickly added. The extensibility is critical since thermal protection systems are becoming increasing complex, e.g. woven carbon polymers. Additionally, as a three-dimensional, unstructured, finite-volume model, Icarus is capable of modeling complex geometries as well as multi-dimensional physics, which have been shown to be important in some scenarios and are not captured by one-dimensional models. In this paper, the mathematical and numerical formulation is presented followed by a discussion of the software architecture and some preliminary verification and validation studies.

Generalised additive modelling approach to the fermentation process of glutamate.

PubMed

Liu, Chun-Bo; Li, Yun; Pan, Feng; Shi, Zhong-Ping

2011-03-01

In this work, generalised additive models (GAMs) were used for the first time to model the fermentation of glutamate (Glu). It was found that three fermentation parameters fermentation time (T), dissolved oxygen (DO) and oxygen uptake rate (OUR) could capture 97% variance of the production of Glu during the fermentation process through a GAM model calibrated using online data from 15 fermentation experiments. This model was applied to investigate the individual and combined effects of T, DO and OUR on the production of Glu. The conditions to optimize the fermentation process were proposed based on the simulation study from this model. Results suggested that the production of Glu can reach a high level by controlling concentration levels of DO and OUR to the proposed optimization conditions during the fermentation process. The GAM approach therefore provides an alternative way to model and optimize the fermentation process of Glu. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Evaluation of airborne lidar data to predict vegetation Presence/Absence

USGS Publications Warehouse

Palaseanu-Lovejoy, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, C.W.

2009-01-01

This study evaluates the capabilities of the Experimental Advanced Airborne Research Lidar (EAARL) in delineating vegetation assemblages in Jean Lafitte National Park, Louisiana. Five-meter-resolution grids of bare earth, canopy height, canopy-reflection ratio, and height of median energy were derived from EAARL data acquired in September 2006. Ground-truth data were collected along transects to assess species composition, canopy cover, and ground cover. To decide which model is more accurate, comparisons of general linear models and generalized additive models were conducted using conventional evaluation methods (i.e., sensitivity, specificity, Kappa statistics, and area under the curve) and two new indexes, net reclassification improvement and integrated discrimination improvement. Generalized additive models were superior to general linear models in modeling presence/absence in training vegetation categories, but no statistically significant differences between the two models were achieved in determining the classification accuracy at validation locations using conventional evaluation methods, although statistically significant improvements in net reclassifications were observed. ?? 2009 Coastal Education and Research Foundation.

Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

NASA Astrophysics Data System (ADS)

Saleh Ahmar, Ansari; Guritno, Suryo; Abdurakhman; Rahman, Abdul; Awi; Alimuddin; Minggi, Ilham; Arif Tiro, M.; Kasim Aidid, M.; Annas, Suwardi; Utami Sutiksno, Dian; Ahmar, Dewi S.; Ahmar, Kurniawan H.; Abqary Ahmar, A.; Zaki, Ahmad; Abdullah, Dahlan; Rahim, Robbi; Nurdiyanto, Heri; Hidayat, Rahmat; Napitupulu, Darmawan; Simarmata, Janner; Kurniasih, Nuning; Andretti Abdillah, Leon; Pranolo, Andri; Haviluddin; Albra, Wahyudin; Arifin, A. Nurani M.

2018-01-01

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression Zt = 0,106+0,204Z t-1+0,401Z t-2-329X 1(t)+115X 2(t)+35,9X 3(t) and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.

Stoichiometry and kinetics of the anaerobic ammonium oxidation (Anammox) with trace hydrazine addition.

PubMed

Yao, Zongbao; Lu, Peili; Zhang, Daijun; Wan, Xinyu; Li, Yulian; Peng, Shuchan

2015-12-01

Purpose of this study is to investigate the stoichiometry and kinetics of anaerobic ammonium oxidation (Anammox) with trace hydrazine addition. The stoichiometry was established based on the electron balance of Anammox process with trace N2H4 addition. The stoichiometric coefficients were determined by the proton consumption and the changes in substrates and products. It was found that trace N2H4 addition can increase the yield of Anammox bacteria (AnAOB) and reduce NO3(-) yield, which enhances the Anammox. Subsequently, kinetic model of Anammox with trace N2H4 addition was developed, and the parameters of the anaerobic degradation model of N2H4 were obtained for the first time. The maximum specific substrate utilization rate, half-saturation constant and inhibition constant of N2H4 were 25.09mgN/g VSS/d, 10.42mgN/L and 1393.88mgN/L, respectively. These kinetic parameters might provide important information for the engineering applications of Anammox with trace N2H4 addition. Copyright © 2015 Elsevier Ltd. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models.

PubMed

Bignardi, A B; El Faro, L; Cardoso, V L; Machado, P F; Albuquerque, L G

2009-09-01

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Development and validation of age-dependent FE human models of a mid-sized male thorax.

PubMed

El-Jawahri, Raed E; Laituri, Tony R; Ruan, Jesse S; Rouhana, Stephen W; Barbat, Saeed D

2010-11-01

The increasing number of people over 65 years old (YO) is an important research topic in the area of impact biomechanics, and finite element (FE) modeling can provide valuable support for related research. There were three objectives of this study: (1) Estimation of the representative age of the previously-documented Ford Human Body Model (FHBM) -- an FE model which approximates the geometry and mass of a mid-sized male, (2) Development of FE models representing two additional ages, and (3) Validation of the resulting three models to the extent possible with respect to available physical tests. Specifically, the geometry of the model was compared to published data relating rib angles to age, and the mechanical properties of different simulated tissues were compared to a number of published aging functions. The FHBM was determined to represent a 53-59 YO mid-sized male. The aforementioned aging functions were used to develop FE models representing two additional ages: 35 and 75 YO. The rib model was validated against human rib specimens and whole rib tests, under different loading conditions, with and without modeled fracture. In addition, the resulting three age-dependent models were validated by simulating cadaveric tests of blunt and sled impacts. The responses of the models, in general, were within the cadaveric response corridors. When compared to peak responses from individual cadavers similar in size and age to the age-dependent models, some responses were within one standard deviation of the test data. All the other responses, but one, were within two standard deviations.

Flood loss model transfer: on the value of additional data

NASA Astrophysics Data System (ADS)

Schröter, Kai; Lüdtke, Stefan; Vogel, Kristin; Kreibich, Heidi; Thieken, Annegret; Merz, Bruno

2017-04-01

The transfer of models across geographical regions and flood events is a key challenge in flood loss estimation. Variations in local characteristics and continuous system changes require regional adjustments and continuous updating with current evidence. However, acquiring data on damage influencing factors is expensive and therefore assessing the value of additional data in terms of model reliability and performance improvement is of high relevance. The present study utilizes empirical flood loss data on direct damage to residential buildings available from computer aided telephone interviews that were carried out after the floods in 2002, 2005, 2006, 2010, 2011 and 2013 mainly in the Elbe and Danube catchments in Germany. Flood loss model performance is assessed for incrementally increased numbers of loss data which are differentiated according to region and flood event. Two flood loss modeling approaches are considered: (i) a multi-variable flood loss model approach using Random Forests and (ii) a uni-variable stage damage function. Both model approaches are embedded in a bootstrapping process which allows evaluating the uncertainty of model predictions. Predictive performance of both models is evaluated with regard to mean bias, mean absolute and mean squared errors, as well as hit rate and sharpness. Mean bias and mean absolute error give information about the accuracy of model predictions; mean squared error and sharpness about precision and hit rate is an indicator for model reliability. The results of incremental, regional and temporal updating demonstrate the usefulness of additional data to improve model predictive performance and increase model reliability, particularly in a spatial-temporal transfer setting.

Investigating the chemical changes of chlorogenic acids during coffee brewing: conjugate addition of water to the olefinic moiety of chlorogenic acids and their quinides.

PubMed

Matei, Marius Febi; Jaiswal, Rakesh; Kuhnert, Nikolai

2012-12-12

Coffee is one of the most popular and consumed beverages in the world and is associated with a series of benefits for human health. In this study we focus on the reactivity of chlorogenic acids, the most abundant secondary metabolites in coffee, during the coffee brewing process. We report on the hydroxylation of the chlorogenic acid cinnamoyl substituent by conjugate addition of water to form 3-hydroxydihydrocaffeic acid derivatives using a series of model compounds including monocaffeoyl and dicaffeoylquinic acids and quinic acid lactones. The regiochemistry of conjugate addition was established based on targeted tandem MS experiments. Following conjugate addition of water a reversible water elimination yielding cis-cinnamoyl derivatives accompanied by acyl migration products was observed in model systems. We also report the formation of all of these derivatives during the coffee brewing process.

Assessment of food intake input distributions for use in probabilistic exposure assessments of food additives.

PubMed

Gilsenan, M B; Lambe, J; Gibney, M J

2003-11-01

A key component of a food chemical exposure assessment using probabilistic analysis is the selection of the most appropriate input distribution to represent exposure variables. The study explored the type of parametric distribution that could be used to model variability in food consumption data likely to be included in a probabilistic exposure assessment of food additives. The goodness-of-fit of a range of continuous distributions to observed data of 22 food categories expressed as average daily intakes among consumers from the North-South Ireland Food Consumption Survey was assessed using the BestFit distribution fitting program. The lognormal distribution was most commonly accepted as a plausible parametric distribution to represent food consumption data when food intakes were expressed as absolute intakes (16/22 foods) and as intakes per kg body weight (18/22 foods). Results from goodness-of-fit tests were accompanied by lognormal probability plots for a number of food categories. The influence on food additive intake of using a lognormal distribution to model food consumption input data was assessed by comparing modelled intake estimates with observed intakes. Results from the present study advise some level of caution about the use of a lognormal distribution as a mode of input for food consumption data in probabilistic food additive exposure assessments and the results highlight the need for further research in this area.

Comparison of prosthetic models produced by traditional and additive manufacturing methods.

PubMed

Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong; Kim, Woong-Chul

2015-08-01

The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). The mean marginal gaps and internal gaps showed significant differences according to tooth type (P<.001 and P<.001, respectively) and manufacturing method (P<.037 and P<.001, respectively). Micro-SLA did not show any significant difference from CLWT regarding mean marginal gap compared to the WBM and MJM methods. The mean values of gaps resulting from the four different manufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing.

Effects of methyl mercury in combination with polychlorinated biphenyls and brominated flame retardants on the uptake of glutamate in rat brain synaptosomes: a mathematical approach for the study of mixtures.

PubMed

Stavenes Andersen, Ingrid; Voie, Oyvind Albert; Fonnum, Frode; Mariussen, Espen

2009-11-01

Regulatory limit values for toxicants are in general determined by the toxicology of the single compounds. However, little is known about their combined effects. Methyl mercury (MeHg), polychlorinated biphenyls (PCBs), and brominated flame retardants (BFRs) are dominant contaminants in the environment and food. MeHg is a well known neurotoxicant, especially affecting the developing brain. There is increasing evidence that PCB and BFRs also have neurotoxic effects. An enhanced effect of these toxicants, due to either synergistic or additive effects, would be considered as a risk for the fetal development. Here we studied the combinatorial effects of MeHg in combination with PCB or BFR on the reuptake of glutamate in synaptosomes. To provide the optimal conclusion regarding type of interaction, we have analyzed the data using two mathematical models, the Löewe model of additivity and Bliss' model of independent action. Binary and ternary mixtures in different proportions were made. The toxicants had primarily additive effects, as shown with both models, although tendencies towards synergism were observed. MeHg was by far the most potent inhibitor of uptake with an EC(50) value of 0.33 microM. A reconstituted mixture from a relevant fish sample was made in order to elucidate which chemical was responsible for the observed effect. Some interaction was experienced between PCB and MeHg, but in general MeHg seemed to explain the observed effect. We also show that mixture effects should not be assessed by effect addition.

Spatio-temporal Bayesian model selection for disease mapping

PubMed Central

Carroll, R; Lawson, AB; Faes, C; Kirby, RS; Aregay, M; Watjou, K

2016-01-01

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor. PMID:28070156

Aortic dissection simulation models for clinical support: fluid-structure interaction vs. rigid wall models.

PubMed

Alimohammadi, Mona; Sherwood, Joseph M; Karimpour, Morad; Agu, Obiekezie; Balabani, Stavroula; Díaz-Zuccarini, Vanessa

2015-04-15

The management and prognosis of aortic dissection (AD) is often challenging and the use of personalised computational models is being explored as a tool to improve clinical outcome. Including vessel wall motion in such simulations can provide more realistic and potentially accurate results, but requires significant additional computational resources, as well as expertise. With clinical translation as the final aim, trade-offs between complexity, speed and accuracy are inevitable. The present study explores whether modelling wall motion is worth the additional expense in the case of AD, by carrying out fluid-structure interaction (FSI) simulations based on a sample patient case. Patient-specific anatomical details were extracted from computed tomography images to provide the fluid domain, from which the vessel wall was extrapolated. Two-way fluid-structure interaction simulations were performed, with coupled Windkessel boundary conditions and hyperelastic wall properties. The blood was modelled using the Carreau-Yasuda viscosity model and turbulence was accounted for via a shear stress transport model. A simulation without wall motion (rigid wall) was carried out for comparison purposes. The displacement of the vessel wall was comparable to reports from imaging studies in terms of intimal flap motion and contraction of the true lumen. Analysis of the haemodynamics around the proximal and distal false lumen in the FSI model showed complex flow structures caused by the expansion and contraction of the vessel wall. These flow patterns led to significantly different predictions of wall shear stress, particularly its oscillatory component, which were not captured by the rigid wall model. Through comparison with imaging data, the results of the present study indicate that the fluid-structure interaction methodology employed herein is appropriate for simulations of aortic dissection. Regions of high wall shear stress were not significantly altered by the wall motion, however, certain collocated regions of low and oscillatory wall shear stress which may be critical for disease progression were only identified in the FSI simulation. We conclude that, if patient-tailored simulations of aortic dissection are to be used as an interventional planning tool, then the additional complexity, expertise and computational expense required to model wall motion is indeed justified.

Diagnostic utility of appetite loss in addition to existing prediction models for community-acquired pneumonia in the elderly: a prospective diagnostic study in acute care hospitals in Japan.

PubMed

Takada, Toshihiko; Yamamoto, Yosuke; Terada, Kazuhiko; Ohta, Mitsuyasu; Mikami, Wakako; Yokota, Hajime; Hayashi, Michio; Miyashita, Jun; Azuma, Teruhisa; Fukuma, Shingo; Fukuhara, Shunichi

2017-11-08

Diagnosis of community-acquired pneumonia (CAP) in the elderly is often delayed because of atypical presentation and non-specific symptoms, such as appetite loss, falls and disturbance in consciousness. The aim of this study was to investigate the external validity of existing prediction models and the added value of the non-specific symptoms for the diagnosis of CAP in elderly patients. Prospective cohort study. General medicine departments of three teaching hospitals in Japan. A total of 109 elderly patients who consulted for upper respiratory symptoms between 1 October 2014 and 30 September 2016. The reference standard for CAP was chest radiograph evaluated by two certified radiologists. The existing models were externally validated for diagnostic performance by calibration plot and discrimination. To evaluate the additional value of the non-specific symptoms to the existing prediction models, we developed an extended logistic regression model. Calibration, discrimination, category-free net reclassification improvement (NRI) and decision curve analysis (DCA) were investigated in the extended model. Among the existing models, the model by van Vugt demonstrated the best performance, with an area under the curve of 0.75(95% CI 0.63 to 0.88); calibration plot showed good fit despite a significant Hosmer-Lemeshow test (p=0.017). Among the non-specific symptoms, appetite loss had positive likelihood ratio of 3.2 (2.0-5.3), negative likelihood ratio of 0.4 (0.2-0.7) and OR of 7.7 (3.0-19.7). Addition of appetite loss to the model by van Vugt led to improved calibration at p=0.48, NRI of 0.53 (p=0.019) and higher net benefit by DCA. Information on appetite loss improved the performance of an existing model for the diagnosis of CAP in the elderly. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Incorporating neurophysiological concepts in mathematical thermoregulation models

NASA Astrophysics Data System (ADS)

Kingma, Boris R. M.; Vosselman, M. J.; Frijns, A. J. H.; van Steenhoven, A. A.; van Marken Lichtenbelt, W. D.

2014-01-01

Skin blood flow (SBF) is a key player in human thermoregulation during mild thermal challenges. Various numerical models of SBF regulation exist. However, none explicitly incorporates the neurophysiology of thermal reception. This study tested a new SBF model that is in line with experimental data on thermal reception and the neurophysiological pathways involved in thermoregulatory SBF control. Additionally, a numerical thermoregulation model was used as a platform to test the function of the neurophysiological SBF model for skin temperature simulation. The prediction-error of the SBF-model was quantified by root-mean-squared-residual (RMSR) between simulations and experimental measurement data. Measurement data consisted of SBF (abdomen, forearm, hand), core and skin temperature recordings of young males during three transient thermal challenges (1 development and 2 validation). Additionally, ThermoSEM, a thermoregulation model, was used to simulate body temperatures using the new neurophysiological SBF-model. The RMSR between simulated and measured mean skin temperature was used to validate the model. The neurophysiological model predicted SBF with an accuracy of RMSR < 0.27. Tskin simulation results were within 0.37 °C of the measured mean skin temperature. This study shows that (1) thermal reception and neurophysiological pathways involved in thermoregulatory SBF control can be captured in a mathematical model, and (2) human thermoregulation models can be equipped with SBF control functions that are based on neurophysiology without loss of performance. The neurophysiological approach in modelling thermoregulation is favourable over engineering approaches because it is more in line with the underlying physiology.

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling.

PubMed

Thelen, Brian; French, Nancy H F; Koziol, Benjamin W; Billmire, Michael; Owen, Robert Chris; Johnson, Jeffrey; Ginsberg, Michele; Loboda, Tatiana; Wu, Shiliang

2013-11-05

A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data.

The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finley, Cathy

2014-04-30

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements inmore » wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.« less

Parameters and pitfalls to consider in the conduct of food additive research, Carrageenan as a case study.

PubMed

Weiner, Myra L

2016-01-01

This paper provides guidance on the conduct of new in vivo and in vitro studies on high molecular weight food additives, with carrageenan, the widely used food additive, as a case study. It is important to understand the physical/chemical properties and to verify the identity/purity, molecular weight and homogeneity/stability of the additive in the vehicle for oral delivery. The strong binding of CGN to protein in rodent chow or infant formula results in no gastrointestinal tract exposure to free CGN. It is recommended that doses of high Mw non-caloric, non-nutritive additives not exceed 5% by weight of total solid diet to avoid potential nutritional effects. Addition of some high Mw additives at high concentrations to liquid nutritional supplements increases viscosity and may affect palatability, caloric intake and body weight gain. In in vitro studies, the use of well-characterized, relevant cell types and the appropriate composition of the culture media are necessary for proper conduct and interpretation. CGN is bound to media protein and not freely accessible to cells in vitro. Interpretation of new studies on food additives should consider the interaction of food additives with the vehicle components and the appropriateness of the animal or cell model and dose-response. Copyright © 2015 FMC Corporation. Published by Elsevier Ltd.. All rights reserved.

A Posteriori Study of a DNS Database Describing Super critical Binary-Species Mixing

NASA Technical Reports Server (NTRS)

Bellan, Josette; Taskinoglu, Ezgi

2012-01-01

Currently, the modeling of supercritical-pressure flows through Large Eddy Simulation (LES) uses models derived for atmospheric-pressure flows. Those atmospheric-pressure flows do not exhibit the particularities of high densitygradient magnitude features observed both in experiments and simulations of supercritical-pressure flows in the case of two species mixing. To assess whether the current LES modeling is appropriate and if found not appropriate to propose higher-fidelity models, a LES a posteriori study has been conducted for a mixing layer that initially contains different species in the lower and upper streams, and where the initial pressure is larger than the critical pressure of either species. An initially-imposed vorticity perturbation promotes roll-up and a double pairing of four initial span-wise vortices into an ultimate vortex that reaches a transitional state. The LES equations consist of the differential conservation equations coupled with a real-gas equation of state, and the equation set uses transport properties depending on the thermodynamic variables. Unlike all LES models to date, the differential equations contain, additional to the subgrid scale (SGS) fluxes, a new SGS term that is a pressure correction in the momentum equation. This additional term results from filtering of Direct Numerical Simulation (DNS) equations, and represents the gradient of the difference between the filtered pressure and the pressure computed from the filtered flow field. A previous a priori analysis, using a DNS database for the same configuration, found this term to be of leading order in the momentum equation, a fact traced to the existence of high-densitygradient magnitude regions that populated the entire flow; in the study, models were proposed for the SGS fluxes as well as this new term. In the present study, the previously proposed constantcoefficient SGS-flux models of the a priori investigation are tested a posteriori in LES, devoid of or including, the SGS pressure correction term. The present pressure-correction model is different from, and more accurate as well as less computationally intensive than that of the a priori study. The constant-coefficient SGS-flux models encompass the Smagorinsky (SMC), in conjunction with the Yoshizawa (YO) model for the trace, the Gradient (GRC) and the Scale Similarity (SSC) models, all exercised with the a priori study constant coefficients calibrated at the transitional state. The LES comparison is performed with the filtered- and-coarsened (FC) DNS, which represents an ideal LES solution. Expectably, an LES model devoid of SGS terms is shown to be considerably inferior to models containing SGS effects. Among models containing SGS effects, those including the pressure-correction term are substantially superior to those devoid of it. The sensitivity of the predictions to the initial conditions and grid size are also investigated. Thus, it has been discovered that, additional to the atmospheric-pressure models currently used, a new model is necessary to simulate supercritical-pressure flows. This model depends on the thermodynamic characteristics of the chemical species involved.

Development of physical and mathematical models for the Porous Ceramic Tube Plant Nutrification System (PCTPNS)

NASA Technical Reports Server (NTRS)

Tsao, D. Teh-Wei; Okos, M. R.; Sager, J. C.; Dreschel, T. W.

1992-01-01

A physical model of the Porous Ceramic Tube Plant Nutrification System (PCTPNS) was developed through microscopic observations of the tube surface under various operational conditions. In addition, a mathematical model of this system was developed which incorporated the effects of the applied suction pressure, surface tension, and gravitational forces as well as the porosity and physical dimensions of the tubes. The flow of liquid through the PCTPNS was thus characterized for non-biological situations. One of the key factors in the verification of these models is the accurate and rapid measurement of the 'wetness' or holding capacity of the ceramic tubes. This study evaluated a thermistor based moisture sensor device and recommendations for future research on alternative sensing devices are proposed. In addition, extensions of the physical and mathematical models to include the effects of plant physiology and growth are also discussed for future research.

Investigation of Interference Models for RFID Systems.

PubMed

Zhang, Linchao; Ferrero, Renato; Gandino, Filippo; Rebaudengo, Maurizio

2016-02-04

The reader-to-reader collision in an RFID system is a challenging problem for communications technology. In order to model the interference between RFID readers, different interference models have been proposed, mainly based on two approaches: single and additive interference. The former only considers the interference from one reader within a certain range, whereas the latter takes into account the sum of all of the simultaneous interferences in order to emulate a more realistic behavior. Although the difference between the two approaches has been theoretically analyzed in previous research, their effects on the estimated performance of the reader-to-reader anti-collision protocols have not yet been investigated. In this paper, the influence of the interference model on the anti-collision protocols is studied by simulating a representative state-of-the-art protocol. The results presented in this paper highlight that the use of additive models, although more computationally intensive, is mandatory to improve the performance of anti-collision protocols.

Analyzing Seasonal Variations in Suicide With Fourier Poisson Time-Series Regression: A Registry-Based Study From Norway, 1969-2007.

PubMed

Bramness, Jørgen G; Walby, Fredrik A; Morken, Gunnar; Røislien, Jo

2015-08-01

Seasonal variation in the number of suicides has long been acknowledged. It has been suggested that this seasonality has declined in recent years, but studies have generally used statistical methods incapable of confirming this. We examined all suicides occurring in Norway during 1969-2007 (more than 20,000 suicides in total) to establish whether seasonality decreased over time. Fitting of additive Fourier Poisson time-series regression models allowed for formal testing of a possible linear decrease in seasonality, or a reduction at a specific point in time, while adjusting for a possible smooth nonlinear long-term change without having to categorize time into discrete yearly units. The models were compared using Akaike's Information Criterion and analysis of variance. A model with a seasonal pattern was significantly superior to a model without one. There was a reduction in seasonality during the period. Both the model assuming a linear decrease in seasonality and the model assuming a change at a specific point in time were both superior to a model assuming constant seasonality, thus confirming by formal statistical testing that the magnitude of the seasonality in suicides has diminished. The additive Fourier Poisson time-series regression model would also be useful for studying other temporal phenomena with seasonal components. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A physiologically based pharmacokinetic model for developmental exposure to BDE-47 in rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emond, Claude, E-mail: claude.emond@umontreal.c; BioSimulation Consulting Inc., Newark, DE 19711; Raymer, James H.

2010-02-01

Polybrominated diphenyl ethers (PBDEs) are used commercially as additive flame retardants and have been shown to transfer into environmental compartments, where they have the potential to bioaccumulate in wildlife and humans. Of the 209 possible PBDEs, 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) is usually the dominant congener found in human blood and milk samples. BDE-47 has been shown to have endocrine activity and produce developmental, reproductive, and neurotoxic effects. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for BDE-47 in male and female (pregnant and non-pregnant) adult rats to facilitate investigations of developmental exposure. This model consistsmore » of eight compartments: liver, brain, adipose tissue, kidney, placenta, fetus, blood, and the rest of the body. Concentrations of BDE-47 from the literature and from maternal-fetal pharmacokinetic studies conducted at RTI International were used to parameterize and evaluate the model. The results showed that the model simulated BDE-47 tissue concentrations in adult male, maternal, and fetal compartments within the standard deviations of the experimental data. The model's ability to estimate BDE-47 concentrations in the fetus after maternal exposure will be useful to design in utero exposure/effect studies. This PBPK model is the first one designed for any PBDE pharmaco/toxicokinetic description. The next steps will be to expand this model to simulate BDE-47 pharmacokinetics and distributions across species (mice), and then extrapolate it to humans. After mouse and human model development, additional PBDE congeners will be incorporated into the model and simulated as a mixture.« less

Developing a model for agile supply: an empirical study from Iranian pharmaceutical supply chain.

PubMed

Rajabzadeh Ghatari, Ali; Mehralian, Gholamhossein; Zarenezhad, Forouzandeh; Rasekh, Hamid Reza

2013-01-01

Agility is the fundamental characteristic of a supply chain needed for survival in turbulent markets, where environmental forces create additional uncertainty resulting in higher risk in the supply chain management. In addition, agility helps providing the right product, at the right time to the consumer. The main goal of this research is therefore to promote supplier selection in pharmaceutical industry according to the formative basic factors. Moreover, this paper can configure its supply network to achieve the agile supply chain. The present article analyzes the supply part of supply chain based on SCOR model, used to assess agile supply chains by highlighting their specific characteristics and applicability in providing the active pharmaceutical ingredient (API). This methodology provides an analytical modeling; the model enables potential suppliers to be assessed against the multiple criteria using both quantitative and qualitative measures. In addition, for making priority of critical factors, TOPSIS algorithm has been used as a common technique of MADM model. Finally, several factors such as delivery speed, planning and reorder segmentation, trust development and material quantity adjustment are identified and prioritized as critical factors for being agile in supply of API.

Additive interactions between 1-methyl-1,2,3,4-tetrahydroisoquinoline and clobazam in the mouse maximal electroshock-induced tonic seizure model--an isobolographic analysis for parallel dose-response relationship curves.

PubMed

Andres-Mach, Marta; Haratym-Maj, Agnieszka; Zagaja, Mirosław; Luszczki, Jarogniew J

2014-01-01

The aim of this study was to characterize the anticonvulsant effect of 1-methyl-1,2,3,4-tetrahydroisoquinoline (1-MeTHIQ) in combination with clobazam (CLB) in the mouse maximal electroshock-induced seizure (MES) model. The anticonvulsant interaction profile between 1-MeTHIQ and CLB in the mouse MES model was determined using an isobolographic analysis for parallel dose-response relationship curves. Electroconvulsions were produced in albino Swiss mice by a current (sine wave, 25 mA, 500 V, 50 Hz, 0.2-second stimulus duration) delivered via auricular electrodes by a Hugo Sachs generator. There was an additive effect of the combination of 1-MeTHIQ with CLB (at the fixed ratios of 1:3, 1:1 and 3:1) in the mouse MES-induced tonic seizure model. The additive interaction of the combination of 1-MeTHIQ with CLB (at fixed-ratios of 1:3, 1:1 and 3:1) in the mouse MES model seems to be pharmacodynamic in nature and worth of considering in further clinical practice. © 2014 S. Karger AG, Basel.

Developing a Model for Agile Supply: an Empirical Study from Iranian Pharmaceutical Supply Chain

PubMed Central

Rajabzadeh Ghatari, Ali; Mehralian, Gholamhossein; Zarenezhad, Forouzandeh; Rasekh, Hamid Reza

2013-01-01

Agility is the fundamental characteristic of a supply chain needed for survival in turbulent markets, where environmental forces create additional uncertainty resulting in higher risk in the supply chain management. In addition, agility helps providing the right product, at the right time to the consumer. The main goal of this research is therefore to promote supplier selection in pharmaceutical industry according to the formative basic factors. Moreover, this paper can configure its supply network to achieve the agile supply chain. The present article analyzes the supply part of supply chain based on SCOR model, used to assess agile supply chains by highlighting their specific characteristics and applicability in providing the active pharmaceutical ingredient (API). This methodology provides an analytical modeling; the model enables potential suppliers to be assessed against the multiple criteria using both quantitative and qualitative measures. In addition, for making priority of critical factors, TOPSIS algorithm has been used as a common technique of MADM model. Finally, several factors such as delivery speed, planning and reorder segmentation, trust development and material quantity adjustment are identified and prioritized as critical factors for being agile in supply of API. PMID:24250689

X-ray spectroscopic study of amorphous and polycrystalline PbO films, α-PbO, and β-PbO for direct conversion imaging.

PubMed

Qamar, A; LeBlanc, K; Semeniuk, O; Reznik, A; Lin, J; Pan, Y; Moewes, A

2017-10-13

We investigated the electronic structure of Lead Oxide (PbO) - one of the most promising photoconductor materials for direct conversion x-ray imaging detectors, using soft x-ray emission and absorption spectroscopy. Two structural configurations of thin PbO layers, namely the polycrystalline and the amorphous phase, were studied, and compared to the properties of powdered α-PbO and β-PbO samples. In addition, we performed calculations within the framework of density functional theory and found an excellent agreement between the calculated and the measured absorption and emission spectra, which indicates high accuracy of our structural models. Our work provides strong evidence that the electronic structure of PbO layers, specifically the width of the band gap and the presence of additional interband and intraband states in both conduction and valence band, depend on the deposition conditions. We tested several model structures using DFT simulations to understand what the origin of these states is. The presence of O vacancies is the most plausible explanation for these additional electronic states. Several other plausible models were ruled out including interstitial O, dislocated O and the presence of significant lattice stress in PbO.

Event-based design tool for construction site erosion and sediment controls

NASA Astrophysics Data System (ADS)

Trenouth, William R.; Gharabaghi, Bahram

2015-09-01

This paper provides additional discussion surrounding the novel event-based soil loss models developed by Trenouth and Gharabaghi (2015) for the design of erosion and sediment controls (ESCs) for various phases of construction - from pre-development to post-development conditions. The datasets for the study were obtained from three Ontario sites - Greensborough, Cookstown, and Alcona - in addition to datasets mined from the literature for three additional sites - Treynor, Iowa, Coshocton, Ohio and Cordoba, Spain. Model performances were evaluated for each of the study sites, and quantified using commonly-reported statistics. This work is nested within a broader conceptual framework, which includes the estimation of ambient receiving water quality, the prediction of event mean runoff quality for a given design storm, and the calculation of the required level of protection using adequate ESCs to meet receiving water quality guidelines. These models allow design engineers and regulatory agencies to assess the potential risk of ecological damage to receiving waters due to inadequate soil erosion and sediment control practices using dynamic scenario forecasting when considering rapidly changing land use conditions during various phases of construction, typically for a 2- or 5-year design storm return period.

Cardiac Radionuclide Imaging in Rodents: A Review of Methods, Results, and Factors at Play

PubMed Central

Cicone, Francesco; Viertl, David; Quintela Pousa, Ana Maria; Denoël, Thibaut; Gnesin, Silvano; Scopinaro, Francesco; Vozenin, Marie-Catherine; Prior, John O.

2017-01-01

The interest around small-animal cardiac radionuclide imaging is growing as rodent models can be manipulated to allow the simulation of human diseases. In addition to new radiopharmaceuticals testing, often researchers apply well-established probes to animal models, to follow the evolution of the target disease. This reverse translation of standard radiopharmaceuticals to rodent models is complicated by technical shortcomings and by obvious differences between human and rodent cardiac physiology. In addition, radionuclide studies involving small animals are affected by several extrinsic variables, such as the choice of anesthetic. In this paper, we review the major cardiac features that can be studied with classical single-photon and positron-emitting radiopharmaceuticals, namely, cardiac function, perfusion and metabolism, as well as the results and pitfalls of small-animal radionuclide imaging techniques. In addition, we provide a concise guide to the understanding of the most frequently used anesthetics such as ketamine/xylazine, isoflurane, and pentobarbital. We address in particular their mechanisms of action and the potential effects on radionuclide imaging. Indeed, cardiac function, perfusion, and metabolism can all be significantly affected by varying anesthetics and animal handling conditions. PMID:28424774

Temporal and geographical external validation study and extension of the Mayo Clinic prediction model to predict eGFR in the younger population of Swiss ADPKD patients.

PubMed

Girardat-Rotar, Laura; Braun, Julia; Puhan, Milo A; Abraham, Alison G; Serra, Andreas L

2017-07-17

Prediction models in autosomal dominant polycystic kidney disease (ADPKD) are useful in clinical settings to identify patients with greater risk of a rapid disease progression in whom a treatment may have more benefits than harms. Mayo Clinic investigators developed a risk prediction tool for ADPKD patients using a single kidney value. Our aim was to perform an independent geographical and temporal external validation as well as evaluate the potential for improving the predictive performance by including additional information on total kidney volume. We used data from the on-going Swiss ADPKD study from 2006 to 2016. The main analysis included a sample size of 214 patients with Typical ADPKD (Class 1). We evaluated the Mayo Clinic model performance calibration and discrimination in our external sample and assessed whether predictive performance could be improved through the addition of subsequent kidney volume measurements beyond the baseline assessment. The calibration of both versions of the Mayo Clinic prediction model using continuous Height adjusted total kidney volume (HtTKV) and using risk subclasses was good, with R 2 of 78% and 70%, respectively. Accuracy was also good with 91.5% and 88.7% of the predicted within 30% of the observed, respectively. Additional information regarding kidney volume did not substantially improve the model performance. The Mayo Clinic prediction models are generalizable to other clinical settings and provide an accurate tool based on available predictors to identify patients at high risk for rapid disease progression.

Population Pharmacokinetics of Ceftizoxime Administered by Continuous Infusion in Clinically Ill Adult Patients

PubMed Central

Facca, Bryan; Frame, Bill; Triesenberg, Steve

1998-01-01

Ceftizoxime is a widely used beta-lactam antimicrobial agent, but pharmacokinetic data for use with clinically ill patients are lacking. We studied the population pharmacokinetics of ceftizoxime in 72 clinically ill patients at a community-based, university-affiliated hospital. A population pharmacokinetic model for ceftizoxime was created by using a prospective observational design. Ceftizoxime was administered by continuous infusion to treat patients with proven or suspected bacterial infections. While the patients were receiving infusions of ceftizoxime, serum samples were collected for pharmacokinetic analysis with the nonlinear mixed-effect modeling program NONMEM. In addition to clearance and volume of distribution, various comorbidities were examined for their influence on the kinetics. All 72 subjects completed the study, and 114 serum samples were collected. Several demographic and comorbidity variables, namely, age, weight, serum creatinine levels, congestive heart failure, and long-term ventilator dependency, had a significant impact on the estimate for ceftizoxime clearance. A mixture model, or two populations for estimation of ceftizoxime clearance, was discovered. One population presented with an additive clearance component of 1.6 liters per h. In addition, a maximizer function for serum creatinine levels was found. In summary, two models for ceftizoxime clearance, mixture and nonmixture, were found and are presented. Clearance for ceftizoxime can be estimated with commonly available clinical information and the models presented. From the clearance estimates, the dose of ceftizoxime to maintain the desired concentration in serum can be determined. Work is needed to validate the model for drug clearance and to evaluate its predictive performance. PMID:9661021

Association of DPP4 Gene Polymorphisms with Type 2 Diabetes Mellitus in Malaysian Subjects

PubMed Central

Ahmed, Radwan H.; Huri, Hasniza Zaman; Al-Hamodi, Zaid; Salem, Sameer D.; Al-absi, Boshra; Muniandy, Sekaran

2016-01-01

Background Genetic polymorphisms of the Dipeptidyl Peptidase 4 (DPP4) gene may play a role in the etiology of type 2 diabetes mellitus (T2DM). This study aimed to investigate the possible association of single nucleotide polymorphisms (SNPs) of the DPP4 gene in Malaysian subjects with T2DM and evaluated whether they had an effect on the serum levels of soluble dipeptidyl peptidase 4 (sDPP-IV). Method Ten DPP4 SNPs were genotyped by TaqMan genotyping assays in 314 subjects with T2DM and 235 controls. Of these, 71 metabolic syndrome (MetS) subjects were excluded from subsequent analysis. The odds ratios (ORs) and their 95% confidence interval (CIs) were calculated using multiple logistic regression for the association between the SNPs of DPP4 and T2DM. In addition, the serum levels of sDPP-IV were investigated to evaluate the association of the SNPs of DPP4 with the sDPP-IV levels. Results Dominant, recessive, and additive genetic models were employed to test the association of DPP4 polymorphisms with T2DM, after adjusting for age, race, gender and BMI. The rs12617656 was associated with T2DM in Malaysian subjects in the recessive genetic model (OR = 1.98, p = 0.006), dominant model (OR = 1.95, p = 0.008), and additive model (OR = 1.63, p = 0.001). This association was more pronounced among Malaysian Indians, recessive (OR = 3.21, p = 0.019), dominant OR = 3.72, p = 0.003) and additive model (OR = 2.29, p = 0.0009). The additive genetic model showed that DPP4 rs4664443 and rs7633162 polymorphisms were associated with T2DM (OR = 1.53, p = 0.039), and (OR = 1.42, p = 0.020), respectively. In addition, the rs4664443 G>A polymorphism was associated with increased sDPP-IV levels (p = 0.042) in T2DM subjects. Conclusions DPP4 polymorphisms were associated with T2DM in Malaysian subjects, and linked to variations in sDPP-IV levels. In addition, these associations were more pronounced among Malaysian Indian subjects. PMID:27111895

Association of DPP4 Gene Polymorphisms with Type 2 Diabetes Mellitus in Malaysian Subjects.

PubMed

Ahmed, Radwan H; Huri, Hasniza Zaman; Al-Hamodi, Zaid; Salem, Sameer D; Al-Absi, Boshra; Muniandy, Sekaran

2016-01-01

Genetic polymorphisms of the Dipeptidyl Peptidase 4 (DPP4) gene may play a role in the etiology of type 2 diabetes mellitus (T2DM). This study aimed to investigate the possible association of single nucleotide polymorphisms (SNPs) of the DPP4 gene in Malaysian subjects with T2DM and evaluated whether they had an effect on the serum levels of soluble dipeptidyl peptidase 4 (sDPP-IV). Ten DPP4 SNPs were genotyped by TaqMan genotyping assays in 314 subjects with T2DM and 235 controls. Of these, 71 metabolic syndrome (MetS) subjects were excluded from subsequent analysis. The odds ratios (ORs) and their 95% confidence interval (CIs) were calculated using multiple logistic regression for the association between the SNPs of DPP4 and T2DM. In addition, the serum levels of sDPP-IV were investigated to evaluate the association of the SNPs of DPP4 with the sDPP-IV levels. Dominant, recessive, and additive genetic models were employed to test the association of DPP4 polymorphisms with T2DM, after adjusting for age, race, gender and BMI. The rs12617656 was associated with T2DM in Malaysian subjects in the recessive genetic model (OR = 1.98, p = 0.006), dominant model (OR = 1.95, p = 0.008), and additive model (OR = 1.63, p = 0.001). This association was more pronounced among Malaysian Indians, recessive (OR = 3.21, p = 0.019), dominant OR = 3.72, p = 0.003) and additive model (OR = 2.29, p = 0.0009). The additive genetic model showed that DPP4 rs4664443 and rs7633162 polymorphisms were associated with T2DM (OR = 1.53, p = 0.039), and (OR = 1.42, p = 0.020), respectively. In addition, the rs4664443 G>A polymorphism was associated with increased sDPP-IV levels (p = 0.042) in T2DM subjects. DPP4 polymorphisms were associated with T2DM in Malaysian subjects, and linked to variations in sDPP-IV levels. In addition, these associations were more pronounced among Malaysian Indian subjects.

A Longitudinal Field Study Comparing a Multiplicative and an Additive Model of Motivation and Ability. Technical Report No. 11.

ERIC Educational Resources Information Center

Barrett, Gerald V.; And Others

The relative contribution of motivation to ability measures in predicting performance criteria of sales personnel from successive fiscal periods was investigated. In this context, the merits of a multiplicative and additive combination of motivation and ability measures were examined. The relationship between satisfaction and motivation and…

Influence of Additive and Multiplicative Structure and Direction of Comparison on the Reversal Error

ERIC Educational Resources Information Center

González-Calero, José Antonio; Arnau, David; Laserna-Belenguer, Belén

2015-01-01

An empirical study has been carried out to evaluate the potential of word order matching and static comparison as explanatory models of reversal error. Data was collected from 214 undergraduate students who translated a set of additive and multiplicative comparisons expressed in Spanish into algebraic language. In these multiplicative comparisons…

Implementation of Head Start Planned Variation: 1970-1971. Part II.

ERIC Educational Resources Information Center

Lukas, Carol Van Deusen; Wohlleb, Cynthia

This volume of appendices is Part II of a study of program implementation in 12 models of Head Start Planned Variation. It presents details of the data analysis, copies of data collection instruments, and additional analyses and statistics. The appendices are: (A) Analysis of Variance Designs, (B) Copies of Instruments, (C) Additional Analyses,…

Option B+ for the prevention of mother-to-child transmission of HIV infection in developing countries: a review of published cost-effectiveness analyses.

PubMed

Karnon, Jonathan; Orji, Nneka

2016-10-01

To review the published literature on the cost effectiveness of Option B+ (lifelong antiretroviral therapy) for preventing mother-to-child transmission (PMTCT) of HIV during pregnancy and breastfeeding to inform decision making in low- and middle-income countries. PubMed, Scopus, Google scholar and Medline were searched to identify studies of the cost effectiveness of the World Health Organization (WHO) treatment guidelines for PMTCT. Study quality was appraised using the consolidated health economic evaluation reporting standards checklist. Eligible studies were reviewed in detail to assess the relevance and impact of alternative evaluation frameworks, assumptions and input parameter values. Five published cost effectiveness analyses of Option B+ for the PMTCT of HIV were identified. The reported cost-effectiveness of Option B+ varies substantially, with the results of different studies implying that Option B+ is dominant (lower costs, greater benefits), cost-effective (additional benefits at acceptable additional costs) or not cost-effective (additional benefits at unacceptable additional costs). This variation is due to significant differences in model structures and input parameter values. Structural differences were observed around the estimation of programme effects on infants, HIV-infected mothers and their HIV negative partners, over multiple pregnancies, as well assumptions regarding routine access to antiretroviral therapies. Significant differences in key input parameters were observed in transmission rates, intervention costs and effects and downstream cost savings. Across five model-based cost-effectiveness analyses of strategies for the PMTCT of HIV, the most comprehensive analysis reported that option B+ is highly likely to be cost-effective. This evaluation may have been overly favourable towards option B+ with respect to some input parameter values, but potentially important additional benefits were omitted. Decision makers might be best advised to review this analysis, with a view to requesting additional analyses of the model to inform local funding decisions around alternative strategies for the PMTCT of HIV. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A non-ideal model for predicting the effect of dissolved salt on the flash point of solvent mixtures.

PubMed

Liaw, Horng-Jang; Wang, Tzu-Ai

2007-03-06

Flash point is one of the major quantities used to characterize the fire and explosion hazard of liquids. Herein, a liquid with dissolved salt is presented in a salt-distillation process for separating close-boiling or azeotropic systems. The addition of salts to a liquid may reduce fire and explosion hazard. In this study, we have modified a previously proposed model for predicting the flash point of miscible mixtures to extend its application to solvent/salt mixtures. This modified model was verified by comparison with the experimental data for organic solvent/salt and aqueous-organic solvent/salt mixtures to confirm its efficacy in terms of prediction of the flash points of these mixtures. The experimental results confirm marked increases in liquid flash point increment with addition of inorganic salts relative to supplementation with equivalent quantities of water. Based on this evidence, it appears reasonable to suggest potential application for the model in assessment of the fire and explosion hazard for solvent/salt mixtures and, further, that addition of inorganic salts may prove useful for hazard reduction in flammable liquids.

College Student-Athlete Wellness: An Integrative Outreach Model

ERIC Educational Resources Information Center

Beauchemin, James

2014-01-01

College student-athletes face unique stressors that can contribute to compromised well-being. Additionally, there are a variety of barriers that prevent student-athletes from accessing mental health supports. This study used self-report questionnaires and qualitative interviews to examine the impact of an integrative outreach model that…

MODELING FLUX PATHWAYS TO VEGETATION FOR VOLATILE AND SEMI-VOLATILE ORGANIC COMPOUNDS IN A MULTIMEDIA ENVIRONMENT

EPA Science Inventory

This study evaluates the treatment of gas-phase atmospheric deposition in a screening level model of the multimedia environmental distribution of toxics (MEND-TOX). Recent algorithmic additions to MEND-TOX for the estimation of gas-phase deposition velocity over vegetated surf...

Evaluation of the Bess TRS-CA Using the Rasch Rating Scale Model

ERIC Educational Resources Information Center

DiStefano, Christine; Morgan, Grant B.

2010-01-01

This study examined the Behavioral and Emotional Screening System Teacher Rating System for Children and Adolescents (BESS TRS-CA; Kamphaus & Reynolds, 2007) screener using Rasch Rating Scale model (RSM) methodology to provide additional information about psychometric properties of items. Data from the Behavioral Assessment System for Children…

The manufacturing of TiAl6V4 implants using selective laser melting technology

NASA Astrophysics Data System (ADS)

Lykov, P. A.; Baitimerov, R. M.; Panfilov, A. V.; Guz, A. O.

2017-10-01

In this article we study the technique for creating medical implants using additive technologies. A plastic skull model was made. The affected part of the skull was identified and removed. An implant was made of titanium alloy. The implant was installed in the model skull.

An Overview of Exposure Assessment Models Used by the U.S. Environmental Protection Agency

EPA Science Inventory

Models are often used in addition to or in lieu of monitoring data to estimate environmental concentrations and exposures for use in risk assessments or epidemiological studies, and to support regulatory standards and voluntary programs (Jayjock et al., 2007; US EPA, 1989, 1992)....

Theatre for Development as a Model for Transformative Change in Nigeria

ERIC Educational Resources Information Center

Okpadah, Stephen Ogheneruro

2017-01-01

This study examines the role of "theatre for development" (TFD) as a model for social transformation in Nigeria, historicizing its relationship to "community theatre" while illuminating significant innovations in authorship and participation. In addition, the article explores TFD as a relational and performative process in…

Determinants of Fast Food Consumption among Iranian High School Students Based on Planned Behavior Theory

PubMed Central

Sharifirad, Gholamreza; Yarmohammadi, Parastoo; Azadbakht, Leila; Morowatisharifabad, Mohammad Ali; Hassanzadeh, Akbar

2013-01-01

Objective. This study was conducted to identify some factors (beliefs and norms) which are related to fast food consumption among high school students in Isfahan, Iran. We used the framework of the theory planned behavior (TPB) to predict this behavior. Subjects & Methods. Cross-sectional data were available from high school students (n = 521) who were recruited by cluster randomized sampling. All of the students completed a questionnaire assessing variables of standard TPB model including attitude, subjective norms, perceived behavior control (PBC), and the additional variables past behavior, actual behavior control (ABC). Results. The TPB variables explained 25.7% of the variance in intentions with positive attitude as the strongest (β = 0.31, P < 0.001) and subjective norms as the weakest (β = 0.29, P < 0.001) determinant. Concurrently, intentions accounted for 6% of the variance for fast food consumption. Past behavior and ABC accounted for an additional amount of 20.4% of the variance in fast food consumption. Conclusion. Overall, the present study suggests that the TPB model is useful in predicting related beliefs and norms to the fast food consumption among adolescents. Subjective norms in TPB model and past behavior in TPB model with additional variables (past behavior and actual behavior control) were the most powerful predictors of fast food consumption. Therefore, TPB model may be a useful framework for planning intervention programs to reduce fast food consumption by students. PMID:23936635

A reaction-diffusion model of cytosolic hydrogen peroxide.

PubMed

Lim, Joseph B; Langford, Troy F; Huang, Beijing K; Deen, William M; Sikes, Hadley D

2016-01-01

As a signaling molecule in mammalian cells, hydrogen peroxide (H2O2) determines the thiol/disulfide oxidation state of several key proteins in the cytosol. Localization is a key concept in redox signaling; the concentrations of signaling molecules within the cell are expected to vary in time and in space in manner that is essential for function. However, as a simplification, all theoretical studies of intracellular hydrogen peroxide and many experimental studies to date have treated the cytosol as a well-mixed compartment. In this work, we incorporate our previously reported reduced kinetic model of the network of reactions that metabolize hydrogen peroxide in the cytosol into a model that explicitly treats diffusion along with reaction. We modeled a bolus addition experiment, solved the model analytically, and used the resulting equations to quantify the spatiotemporal variations in intracellular H2O2 that result from this kind of perturbation to the extracellular H2O2 concentration. We predict that micromolar bolus additions of H2O2 to suspensions of HeLa cells (0.8 × 10(9)cells/l) result in increases in the intracellular concentration that are localized near the membrane. These findings challenge the assumption that intracellular concentrations of H2O2 are increased uniformly throughout the cell during bolus addition experiments and provide a theoretical basis for differing phenotypic responses of cells to intracellular versus extracellular perturbations to H2O2 levels. Copyright © 2015 Elsevier Inc. All rights reserved.

Neurotoxicological and statistical analyses of a mixture of five organophosphorus pesticides using a ray design.

PubMed

Moser, V C; Casey, M; Hamm, A; Carter, W H; Simmons, J E; Gennings, C

2005-07-01

Environmental exposures generally involve chemical mixtures instead of single chemicals. Statistical models such as the fixed-ratio ray design, wherein the mixing ratio (proportions) of the chemicals is fixed across increasing mixture doses, allows for the detection and characterization of interactions among the chemicals. In this study, we tested for interaction(s) in a mixture of five organophosphorus (OP) pesticides (chlorpyrifos, diazinon, dimethoate, acephate, and malathion). The ratio of the five pesticides (full ray) reflected the relative dietary exposure estimates of the general population as projected by the US EPA Dietary Exposure Evaluation Model (DEEM). A second mixture was tested using the same dose levels of all pesticides, but excluding malathion (reduced ray). The experimental approach first required characterization of dose-response curves for the individual OPs to build a dose-additivity model. A series of behavioral measures were evaluated in adult male Long-Evans rats at the time of peak effect following a single oral dose, and then tissues were collected for measurement of cholinesterase (ChE) activity. Neurochemical (blood and brain cholinesterase [ChE] activity) and behavioral (motor activity, gait score, tail-pinch response score) endpoints were evaluated statistically for evidence of additivity. The additivity model constructed from the single chemical data was used to predict the effects of the pesticide mixture along the full ray (10-450 mg/kg) and the reduced ray (1.75-78.8 mg/kg). The experimental mixture data were also modeled and statistically compared to the additivity models. Analysis of the 5-OP mixture (the full ray) revealed significant deviation from additivity for all endpoints except tail-pinch response. Greater-than-additive responses (synergism) were observed at the lower doses of the 5-OP mixture, which contained non-effective dose levels of each of the components. The predicted effective doses (ED20, ED50) were about half that predicted by additivity, and for brain ChE and motor activity, there was a threshold shift in the dose-response curves. For the brain ChE and motor activity, there was no difference between the full (5-OP mixture) and reduced (4-OP mixture) rays, indicating that malathion did not influence the non-additivity. While the reduced ray for blood ChE showed greater deviation from additivity without malathion in the mixture, the non-additivity observed for the gait score was reversed when malathion was removed. Thus, greater-than-additive interactions were detected for both the full and reduced ray mixtures, and the role of malathion in the interactions varied depending on the endpoint. In all cases, the deviations from additivity occurred at the lower end of the dose-response curves.

Bayesian inference of uncertainties in precipitation-streamflow modeling in a snow affected catchment

NASA Astrophysics Data System (ADS)

Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.

2012-11-01

Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.

[Rapid prototyping in planning reconstructive surgery of the head and neck. Review and evaluation of indications in clinical use].

PubMed

Bill, J S; Reuther, J F

2004-05-01

The aim was to define the indications for use of rapid prototyping models based on data of patients treated with this technique. Since 1987 our department has been developing methods of rapid prototyping in surgery planning. During the study, first the statistical and reproducible anatomical precision of rapid prototyping models was determined on pig skull measurements depending on CT parameters and method of rapid prototyping. Measurements on stereolithography models and on selective laser sintered models confirmed an accuracy of +/-0.88 mm or 2.7% (maximum deviation: -3.0 mm to +3.2 mm) independently from CT parameters or method of rapid prototyping, respectively. With the same precision of models multilayer helical CT with a higher rate is the preferable method of data acquisition compared to conventional helical CT. From 1990 to 2002 in atotal of 122 patients, 127 rapid prototyping models were manufactured: in 112 patients stereolithography models, in 2 patients an additional stereolithography model, in 2 patients an additional selective laser sinter model, in 1 patient an additional milled model, and in 10 patients just a selective laser sinter model. Reconstructive surgery, distraction osteogenesis including midface distraction, and dental implantology are proven to be the major indications for rapid prototyping as confirmed in a review of the literature. Surgery planning on rapid prototyping models should only be used in individual cases due to radiation dose and high costs. Routine use of this technique only seems to be indicated in skull reconstruction and distraction osteogenesis.

Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations.

PubMed

Moghaddar, N; van der Werf, J H J

2017-12-01

The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross-bred sheep populations based on single nucleotide polymorphism (SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on "average information restricted maximum likelihood" using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of prediction was assessed based on a random 10-fold cross-validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross-bred population. In the combined cross-bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross-bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross-bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross-bred population could be overestimated if heterosis is not fitted in the model. © 2017 Blackwell Verlag GmbH.

Assessment of an Explicit Algebraic Reynolds Stress Model

NASA Technical Reports Server (NTRS)

Carlson, Jan-Renee

2005-01-01

This study assesses an explicit algebraic Reynolds stress turbulence model in the in the three-dimensional Reynolds averaged Navier-Stokes (RANS) solver, ISAAC (Integrated Solution Algorithm for Arbitrary Con gurations). Additionally, it compares solutions for two select configurations between ISAAC and the RANS solver PAB3D. This study compares with either direct numerical simulation data, experimental data, or empirical models for several different geometries with compressible, separated, and high Reynolds number flows. In general, the turbulence model matched data or followed experimental trends well, and for the selected configurations, the computational results of ISAAC closely matched those of PAB3D using the same turbulence model.

Application of physiologically based pharmacokinetic modeling in setting acute exposure guideline levels for methylene chloride.

PubMed

Bos, Peter Martinus Jozef; Zeilmaker, Marco Jacob; van Eijkeren, Jan Cornelis Henri

2006-06-01

Acute exposure guideline levels (AEGLs) are derived to protect the human population from adverse health effects in case of single exposure due to an accidental release of chemicals into the atmosphere. AEGLs are set at three different levels of increasing toxicity for exposure durations ranging from 10 min to 8 h. In the AEGL setting for methylene chloride, specific additional topics had to be addressed. This included a change of relevant toxicity endpoint within the 10-min to 8-h exposure time range from central nervous system depression caused by the parent compound to formation of carboxyhemoglobin (COHb) via biotransformation to carbon monoxide. Additionally, the biotransformation of methylene chloride includes both a saturable step as well as genetic polymorphism of the glutathione transferase involved. Physiologically based pharmacokinetic modeling was considered to be the appropriate tool to address all these topics in an adequate way. Two available PBPK models were combined and extended with additional algorithms for the estimation of the maximum COHb levels. The model was validated and verified with data obtained from volunteer studies. It was concluded that all the mentioned topics could be adequately accounted for by the PBPK model. The AEGL values as calculated with the model were substantiated by experimental data with volunteers and are concluded to be practically applicable.

The Cost of an Additional Disability-Free Life Year for Older Americans: 1992–2005

PubMed Central

Cai, Liming

2013-01-01

Objective To estimate the cost of an additional disability-free life year for older Americans in 1992–2005. Data Source This study used 1992–2005 Medicare Current Beneficiary Survey, a longitudinal survey of Medicare beneficiaries with a rotating panel design. Study Design This analysis used multistate life table model to estimate probabilities of transition among a discrete set of health states (nondisabled, disabled, and dead) for two panels of older Americans in 1992 and 2002. Health spending incurred between annual health interviews was estimated by a generalized linear mixed model. Health status, including death, was simulated for each member of the panel using these transition probabilities; the associated health spending was cross-walked to the simulated health changes. Principal Findings Disability-free life expectancy (DFLE) increased significantly more than life expectancy during the study period. Assuming that 50 percent of the gains in DFLE between 1992 and 2005 were attributable to increases in spending, the average discounted cost per additional disability-free life year was $71,000. There were small differences between gender and racial/ethnic groups. Conclusions The cost of an additional disability-free life year was substantially below previous estimates based on mortality trends alone. PMID:22670874

Implementing Generalized Additive Models to Estimate the Expected Value of Sample Information in a Microsimulation Model: Results of Three Case Studies.

PubMed

Rabideau, Dustin J; Pei, Pamela P; Walensky, Rochelle P; Zheng, Amy; Parker, Robert A

2018-02-01

The expected value of sample information (EVSI) can help prioritize research but its application is hampered by computational infeasibility, especially for complex models. We investigated an approach by Strong and colleagues to estimate EVSI by applying generalized additive models (GAM) to results generated from a probabilistic sensitivity analysis (PSA). For 3 potential HIV prevention and treatment strategies, we estimated life expectancy and lifetime costs using the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model, a complex patient-level microsimulation model of HIV progression. We fitted a GAM-a flexible regression model that estimates the functional form as part of the model fitting process-to the incremental net monetary benefits obtained from the CEPAC PSA. For each case study, we calculated the expected value of partial perfect information (EVPPI) using both the conventional nested Monte Carlo approach and the GAM approach. EVSI was calculated using the GAM approach. For all 3 case studies, the GAM approach consistently gave similar estimates of EVPPI compared with the conventional approach. The EVSI behaved as expected: it increased and converged to EVPPI for larger sample sizes. For each case study, generating the PSA results for the GAM approach required 3 to 4 days on a shared cluster, after which EVPPI and EVSI across a range of sample sizes were evaluated in minutes. The conventional approach required approximately 5 weeks for the EVPPI calculation alone. Estimating EVSI using the GAM approach with results from a PSA dramatically reduced the time required to conduct a computationally intense project, which would otherwise have been impractical. Using the GAM approach, we can efficiently provide policy makers with EVSI estimates, even for complex patient-level microsimulation models.

Application of adobe flash media to optimize jigsaw learning model on geometry material

NASA Astrophysics Data System (ADS)

Imam, P.; Imam, S.; Ikrar, P.

2018-05-01

This study aims to determine and describe the effectiveness of the application of adobe flash media for jigsaw learning model on geometry material. In this study, the modified jigsaw learning with adobe flash media is called jigsaw-flash model. This research was conducted in Surakarta. The research method used is mix method research with exploratory sequential strategy. The results of this study indicate that students feel more comfortable and interested in studying geometry material taught by jigsaw-flash model. In addition, students taught using the jigsaw-flash model are more active and motivated than the students who were taught using ordinary jigsaw models. This shows that the use of the jigsaw-flash model can increase student participation and motivation. It can be concluded that the adobe flash media can be used as a solution to reduce the level of student abstraction in learning mathematics.

Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

NASA Astrophysics Data System (ADS)

Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

2010-12-01

Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.

Inactivated Orf virus (Parapoxvirus ovis) elicits antifibrotic activity in models of liver fibrosis.

PubMed

Nowatzky, Janina; Knorr, Andreas; Hirth-Dietrich, Claudia; Siegling, Angela; Volk, Hans-Dieter; Limmer, Andreas; Knolle, Percy; Weber, Olaf

2013-05-01

Inactivated Orf virus (ORFV, Parapoxvirus ovis) demonstrates strong antiviral activity in animal models including a human hepatitis B virus (HBV)-transgenic mouse. In addition, expression of interferon (IFN)-γ and interleukin-10 (IL-10) was induced after administration of inactivated ORFV in these mice. IFN-γ and IL-10 are known to elicit antifibrotic activity. We therefore aimed to study antifibrotic activity of inactivated ORFV in models of liver fibrosis. We characterized ORFV-induced hepatic cytokine expression in rats. We then studied ORFV in two models of liver fibrosis in rats, pig serum-induced liver fibrosis and carbon tetrachloride (CCL4 )-induced liver fibrosis. ORFV induced hepatic expression of IFN-γ and IL-10 in rats. ORFV mediated antifibrotic activity when administrated concomitantly with the fibrosis-inducing agents in both models of liver fibrosis. Importantly, when CCL4 -induced liver fibrosis was already established, ORFV application still showed significant antifibrotic activity. In addition, we were able to demonstrate a direct antifibrotic effect of ORFV on stellate cells. These results establish a potential novel antifibrotic therapeutic approach that not only prevents but also resolves established liver fibrosis. Further studies are required to unravel the details of the mechanisms involved. © 2012 The Japan Society of Hepatology.

The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

PubMed

Clark, Michelle M; Blangero, John; Dyer, Thomas D; Sobel, Eric M; Sinsheimer, Janet S

2016-01-01

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered. © 2015 John Wiley & Sons Ltd/University College London.

A new insight into the dependence of relaxation time on frequency in viscoelastic surfactant solutions: From experimental to modeling study.

PubMed

García, Brayan F; Saraji, Soheil

2018-05-01

The relaxation time in viscoelastic surfactant solutions is a function of temperature, salt/surfactant concentrations, resting conditions, as well as shear frequency. The simplistic assumption of a single and constant relaxation time is not representative of all relaxation modes in these solutions especially at high frequencies. Steady-state and oscillatory measurements are carried out to study the effects of high temperature, concentration and resting condition on the rheology of surfactants/salt mixtures including a non-ionic and a zwitterionic/anionic surfactant system. Furthermore, a novel semi-empirical rheological model is deducted based on Cates theory.This model introduces, for the first time, a frequency-dependence for the continuous relaxation time spectrum. At high temperatures, the non-ionic surfactant become more viscoelastic and the zwitterionic/anionic system loses its viscoelasticity. The addition of surfactant/salt improves the viscoelasticity of both systems, and, for the zwitterionic/anionic mixture, increasing the resting temperature improves its viscoelasticity. In addition, the proposed model significantly improves predictions of traditional Maxwell model for different viscoelastic surfactant solutions (using data from this study and the literature) for a considerable range of surfactant and salt combinations at a wide range of temperature. Copyright © 2018 Elsevier Inc. All rights reserved.

Modelling of individual subject ozone exposure response kinetics.

PubMed

Schelegle, Edward S; Adams, William C; Walby, William F; Marion, M Susan

2012-06-01

A better understanding of individual subject ozone (O(3)) exposure response kinetics will provide insight into how to improve models used in the risk assessment of ambient ozone exposure. To develop a simple two compartment exposure-response model that describes individual subject decrements in forced expiratory volume in one second (FEV(1)) induced by the acute inhalation of O(3) lasting up to 8 h. FEV(1) measurements of 220 subjects who participated in 14 previously completed studies were fit to the model using both particle swarm and nonlinear least squares optimization techniques to identify three subject-specific coefficients producing minimum "global" and local errors, respectively. Observed and predicted decrements in FEV(1) of the 220 subjects were used for validation of the model. Further validation was provided by comparing the observed O(3)-induced FEV(1) decrements in an additional eight studies with predicted values obtained using model coefficients estimated from the 220 subjects used in cross validation. Overall the individual subject measured and modeled FEV(1) decrements were highly correlated (mean R(2) of 0.69 ± 0.24). In addition, it was shown that a matrix of individual subject model coefficients can be used to predict the mean and variance of group decrements in FEV(1). This modeling approach provides insight into individual subject O(3) exposure response kinetics and provides a potential starting point for improving the risk assessment of environmental O(3) exposure.

Development of an integrated generic model for multi-scale assessment of the impacts of agro-ecosystems on major ecosystem services in West Africa.

PubMed

Belem, Mahamadou; Saqalli, Mehdi

2017-11-01

This paper presents an integrated model assessing the impacts of climate change, agro-ecosystem and demographic transition patterns on major ecosystem services in West-Africa along a partial overview of economic aspects (poverty reduction, food self-sufficiency and income generation). The model is based on an agent-based model associated with a soil model and multi-scale spatial model. The resulting Model for West-Africa Agro-Ecosystem Integrated Assessment (MOWASIA) is ecologically generic, meaning it is designed for all sudano-sahelian environments but may then be used as an experimentation facility for testing different scenarios combining ecological and socioeconomic dimensions. A case study in Burkina Faso is examined to assess the environmental and economic performances of semi-continuous and continuous farming systems. Results show that the semi-continuous system using organic fertilizer and fallowing practices contribute better to environment preservation and food security than the more economically performant continuous system. In addition, this study showed that farmers heterogeneity could play an important role in agricultural policies planning and assessment. In addition, the results showed that MOWASIA is an effective tool for designing, analysing the impacts of agro-ecosystems. Copyright © 2017. Published by Elsevier Ltd.

Development of Predictive Models for the Growth Kinetics of Listeria monocytogenes on Fresh Pork under Different Storage Temperatures.

PubMed

Luo, Ke; Hong, Sung-Sam; Wang, Jun; Chung, Mi-Ja; Deog-Hwan, Oh

2015-05-01

This study was conducted to develop a predictive model to estimate the growth of Listeria monocytogenes on fresh pork during storage at constant temperatures (5, 10, 15, 20, 25, 30, and 35°C). The Baranyi model was fitted to growth data (log CFU per gram) to calculate the specific growth rate (SGR) and lag time (LT) with a high coefficient of determination (R(2) > 0.98). As expected, SGR increased with a decline in LT with rising temperatures in all samples. Secondary models were then developed to describe the variation of SGR and LT as a function of temperature. Subsequently, the developed models were validated with additional independent growth data collected at 7, 17, 27, and 37°C and from published reports using proportion of relative errors and proportion of standard error of prediction. The proportion of relative errors of the SGR and LT models developed herein were 0.79 and 0.18, respectively. In addition, the standard error of prediction values of the SGR and LT of L. monocytogenes ranged from 25.7 to 33.1% and from 44.92 to 58.44%, respectively. These results suggest that the model developed in this study was capable of predicting the growth of L. monocytogenes under various isothermal conditions.

Enlarged leukocyte referent libraries can explain additional variance in blood-based epigenome-wide association studies.

PubMed

Kim, Stephanie; Eliot, Melissa; Koestler, Devin C; Houseman, Eugene A; Wetmur, James G; Wiencke, John K; Kelsey, Karl T

2016-09-01

We examined whether variation in blood-based epigenome-wide association studies could be more completely explained by augmenting existing reference DNA methylation libraries. We compared existing and enhanced libraries in predicting variability in three publicly available 450K methylation datasets that collected whole-blood samples. Models were fit separately to each CpG site and used to estimate the additional variability when adjustments for cell composition were made with each library. Calculation of the mean difference in the CpG-specific residual sums of squares error between models for an arthritis, aging and metabolic syndrome dataset, indicated that an enhanced library explained significantly more variation across all three datasets (p < 10(-3)). Pathologically important immune cell subtypes can explain important variability in epigenome-wide association studies done in blood.

IT vendor selection model by using structural equation model & analytical hierarchy process

NASA Astrophysics Data System (ADS)

Maitra, Sarit; Dominic, P. D. D.

2012-11-01

Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

Accelerated test system strength models based on Birnbaum-Saunders distribution: a complete Bayesian analysis and comparison.

PubMed

Upadhyay, S K; Mukherjee, Bhaswati; Gupta, Ashutosh

2009-09-01

Several models for studies related to tensile strength of materials are proposed in the literature where the size or length component has been taken to be an important factor for studying the specimens' failure behaviour. An important model, developed on the basis of cumulative damage approach, is the three-parameter extension of the Birnbaum-Saunders fatigue model that incorporates size of the specimen as an additional variable. This model is a strong competitor of the commonly used Weibull model and stands better than the traditional models, which do not incorporate the size effect. The paper considers two such cumulative damage models, checks their compatibility with a real dataset, compares them with some of the recent toolkits, and finally recommends a model, which appears an appropriate one. Throughout the study is Bayesian based on Markov chain Monte Carlo simulation.

Age-Related Behavioral Phenotype of an Astrocytic Monoamine Oxidase-B Transgenic Mouse Model of Parkinson’s Disease

PubMed Central

Lieu, Christopher A.; Chinta, Shankar J.; Rane, Anand; Andersen, Julie K.

2013-01-01

We have previously shown that increases in astrocytic monoamine oxidase-B (MAO-B) expression, mimicking that which occurs with aging and in neurodegenerative disease, in a doxycycline (dox)-inducible transgenic mouse model evokes neuropathological similarities to what is observed in the human parkinsonian brain. Additional behavioral and neuropathological studies could provide further validation for its usage as a model for Parkinson’s disease (PD). In the present study, we utilized a battery of behavioral tests to evaluate age-related phenotype in this model. In the open field test, we found that dox-induction impaired motor ability with decreases in movement and ambulatory function as well as diminished stereotypical, repetitive movement episodes in both young and old mice. Older mice also showed decreased motor performance in the pole test when compared to younger mice. Furthermore, dox-induced older mice displayed severe hindlimb clasping and the most significant loss of dopamine (DA) in the striatum when compared to young and non-induced animals. Additionally, increased MAO-B activity significantly correlated with decreased expression of striatal DA. The results of our study further confirms that the dox-inducible astrocytic MAO-B transgenic mouse displays similar age-related behavioral and neuropathological features to other models of PD, and could serve as a useful tool to study PD pathophysiology and for the evaluation of therapeutic interventions. PMID:23326597

Age-related behavioral phenotype of an astrocytic monoamine oxidase-B transgenic mouse model of Parkinson's disease.

PubMed

Lieu, Christopher A; Chinta, Shankar J; Rane, Anand; Andersen, Julie K

2013-01-01

We have previously shown that increases in astrocytic monoamine oxidase-B (MAO-B) expression, mimicking that which occurs with aging and in neurodegenerative disease, in a doxycycline (dox)-inducible transgenic mouse model evokes neuropathological similarities to what is observed in the human parkinsonian brain. Additional behavioral and neuropathological studies could provide further validation for its usage as a model for Parkinson's disease (PD). In the present study, we utilized a battery of behavioral tests to evaluate age-related phenotype in this model. In the open field test, we found that dox-induction impaired motor ability with decreases in movement and ambulatory function as well as diminished stereotypical, repetitive movement episodes in both young and old mice. Older mice also showed decreased motor performance in the pole test when compared to younger mice. Furthermore, dox-induced older mice displayed severe hindlimb clasping and the most significant loss of dopamine (DA) in the striatum when compared to young and non-induced animals. Additionally, increased MAO-B activity significantly correlated with decreased expression of striatal DA. The results of our study further confirms that the dox-inducible astrocytic MAO-B transgenic mouse displays similar age-related behavioral and neuropathological features to other models of PD, and could serve as a useful tool to study PD pathophysiology and for the evaluation of therapeutic interventions.

Benefits of Applying Hierarchical Models to the Empirical Green's Function Approach

NASA Astrophysics Data System (ADS)

Denolle, M.; Van Houtte, C.

2017-12-01

Stress drops calculated from source spectral studies currently show larger variability than what is implied by empirical ground motion models. One of the potential origins of the inflated variability is the simplified model-fitting techniques used in most source spectral studies. This study improves upon these existing methods, and shows that the fitting method may explain some of the discrepancy. In particular, Bayesian hierarchical modelling is shown to be a method that can reduce bias, better quantify uncertainties and allow additional effects to be resolved. The method is applied to the Mw7.1 Kumamoto, Japan earthquake, and other global, moderate-magnitude, strike-slip earthquakes between Mw5 and Mw7.5. It is shown that the variation of the corner frequency, fc, and the falloff rate, n, across the focal sphere can be reliably retrieved without overfitting the data. Additionally, it is shown that methods commonly used to calculate corner frequencies can give substantial biases. In particular, if fc were calculated for the Kumamoto earthquake using a model with a falloff rate fixed at 2 instead of the best fit 1.6, the obtained fc would be as large as twice its realistic value. The reliable retrieval of the falloff rate allows deeper examination of this parameter for a suite of global, strike-slip earthquakes, and its scaling with magnitude. The earthquake sequences considered in this study are from Japan, New Zealand, Haiti and California.

Estimating gestational age at birth from fundal height and additional anthropometrics: a prospective cohort study.

PubMed

Pugh, S J; Ortega-Villa, A M; Grobman, W; Newman, R B; Owen, J; Wing, D A; Albert, P S; Grantz, K L

2018-02-23

Accurate assessment of gestational age (GA) is critical to paediatric care, but is limited in developing countries without access to ultrasound. Our objectives were to assess the accuracy of prediction of GA at birth and preterm birth classification using routinely collected anthropometry measures. Prospective cohort study. United States. A total of 2334 non-obese and 468 obese pregnant women. Enrolment GA was determined based on last menstrual period, confirmed by first-trimester ultrasound. Maternal anthropometry and fundal height (FH) were measured by a standardised protocol at study visits; FH alone was additionally abstracted from medical charts. Neonatal anthropometry measurements were obtained at birth. To estimate GA at delivery, we developed three predictor models using longitudinal FH alone and with maternal and neonatal anthropometry. For all predictors, we repeatedly sampled observations to construct training (60%) and test (40%) sets. Linear mixed models incorporated longitudinal maternal anthropometry and a shared parameter model incorporated neonatal anthropometry. We assessed models' accuracy under varied scenarios. Estimated GA at delivery. Prediction error for various combinations of anthropometric measures ranged between 13.9 and 14.9 days. Longitudinal FH alone predicted GA within 14.9 days with relatively stable prediction errors across individual race/ethnicities [whites (13.9 days), blacks (15.1 days), Hispanics (15.5 days) and Asians (13.1 days)], and correctly identified 75% of preterm births. The model was robust to additional scenarios. In low-risk, non-obese women, longitudinal FH measures alone can provide a reasonably accurate assessment of GA when ultrasound measures are not available. Longitudinal fundal height alone predicts gestational age at birth when ultrasound measures are unavailable. © 2018 Royal College of Obstetricians and Gynaecologists.

Failure mechanisms of additively manufactured porous biomaterials: Effects of porosity and type of unit cell.

PubMed

Kadkhodapour, J; Montazerian, H; Darabi, A Ch; Anaraki, A P; Ahmadi, S M; Zadpoor, A A; Schmauder, S

2015-10-01

Since the advent of additive manufacturing techniques, regular porous biomaterials have emerged as promising candidates for tissue engineering scaffolds owing to their controllable pore architecture and feasibility in producing scaffolds from a variety of biomaterials. The architecture of scaffolds could be designed to achieve similar mechanical properties as in the host bone tissue, thereby avoiding issues such as stress shielding in bone replacement procedure. In this paper, the deformation and failure mechanisms of porous titanium (Ti6Al4V) biomaterials manufactured by selective laser melting from two different types of repeating unit cells, namely cubic and diamond lattice structures, with four different porosities are studied. The mechanical behavior of the above-mentioned porous biomaterials was studied using finite element models. The computational results were compared with the experimental findings from a previous study of ours. The Johnson-Cook plasticity and damage model was implemented in the finite element models to simulate the failure of the additively manufactured scaffolds under compression. The computationally predicted stress-strain curves were compared with the experimental ones. The computational models incorporating the Johnson-Cook damage model could predict the plateau stress and maximum stress at the first peak with less than 18% error. Moreover, the computationally predicted deformation modes were in good agreement with the results of scaling law analysis. A layer-by-layer failure mechanism was found for the stretch-dominated structures, i.e. structures made from the cubic unit cell, while the failure of the bending-dominated structures, i.e. structures made from the diamond unit cells, was accompanied by the shearing bands of 45°. Copyright © 2015 Elsevier Ltd. All rights reserved.

The perceived impact of the group practice model on enhancing interpersonal skills of predoctoral dental students

PubMed Central

Errante, Margaret R; Gill, Gurjinder S; Rodriguez, Tobias E

2018-01-01

Purpose The purpose of this study was to assess if a clinical group practice model has an impact on enhancing the interpersonal skills of predoctoral dental students, what factors may influence the development of these skills, and what, if any, are innovative and technological solutions that can potentially influence interpersonal skills in predoctoral dental students. Methods This study surveyed the faculty responsible for teaching the dental students in a recently developed group practice model. Out of 18 eligible group practice leaders at one US dental school, 17 respondents (94.4%) completed the survey. In addition, this study asked the faculty to provide qualitative response and recommendations to improve interpersonal skills. Based on the feedback, a focus group was conducted to explore opportunities to further enhance the skills. Results The results of the study suggest that the group practice model has a positive and distinct impact on the development of overall interpersonal skills for students. Further research suggests that the greatest impacted areas of personal development are critical thinking skills and teamwork. However, as a way to make the model more effectual, most faculty suggested the need for additional time, for both students and faculty. To some extent, using technology and innovative teaching pedagogies could potentially address the challenge of limited time. Conclusion Based on the results of the survey, one may conclude that with adequate design and conditions, the group practice model can have a positive effect on the interpersonal skills of its students. PMID:29720884

The perceived impact of the group practice model on enhancing interpersonal skills of predoctoral dental students.

PubMed

Errante, Margaret R; Gill, Gurjinder S; Rodriguez, Tobias E

2018-01-01

The purpose of this study was to assess if a clinical group practice model has an impact on enhancing the interpersonal skills of predoctoral dental students, what factors may influence the development of these skills, and what, if any, are innovative and technological solutions that can potentially influence interpersonal skills in predoctoral dental students. This study surveyed the faculty responsible for teaching the dental students in a recently developed group practice model. Out of 18 eligible group practice leaders at one US dental school, 17 respondents (94.4%) completed the survey. In addition, this study asked the faculty to provide qualitative response and recommendations to improve interpersonal skills. Based on the feedback, a focus group was conducted to explore opportunities to further enhance the skills. The results of the study suggest that the group practice model has a positive and distinct impact on the development of overall interpersonal skills for students. Further research suggests that the greatest impacted areas of personal development are critical thinking skills and teamwork. However, as a way to make the model more effectual, most faculty suggested the need for additional time, for both students and faculty. To some extent, using technology and innovative teaching pedagogies could potentially address the challenge of limited time. Based on the results of the survey, one may conclude that with adequate design and conditions, the group practice model can have a positive effect on the interpersonal skills of its students.

A systemic approach for modeling biological evolution using Parallel DEVS.

PubMed

Heredia, Daniel; Sanz, Victorino; Urquia, Alfonso; Sandín, Máximo

2015-08-01

A new model for studying the evolution of living organisms is proposed in this manuscript. The proposed model is based on a non-neodarwinian systemic approach. The model is focused on considering several controversies and open discussions about modern evolutionary biology. Additionally, a simplification of the proposed model, named EvoDEVS, has been mathematically described using the Parallel DEVS formalism and implemented as a computer program using the DEVSLib Modelica library. EvoDEVS serves as an experimental platform to study different conditions and scenarios by means of computer simulations. Two preliminary case studies are presented to illustrate the behavior of the model and validate its results. EvoDEVS is freely available at http://www.euclides.dia.uned.es. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Hybrid Soft Soil Tire Model (HSSTM). Part 1: Tire Material and Structure Modeling

DTIC Science & Technology

2015-04-28

commercially available vehicle simulation packages. Model parameters are obtained using a validated finite element tire model, modal analysis, and other...design of experiment matrix. This data, in addition to modal analysis data were used to validate the tire model. Furthermore, to study the validity...é ë ê ê ê ê ê ê ê ù û ú ú ú ú ú ú ú (78) The applied forces to the rim center consist of the axle forces and suspension forces: FFF Gsuspension G

Impact of trace element additives on anaerobic digestion of sewage sludge with in-situ carbon dioxide sequestration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linville, Jessica L.; Shen, Yanwen; Schoene, Robin P.

Anaerobic digestion (AD) of sludge at wastewater treatment plants can benefit from addition of essential trace metals such as iron, nickel and cobalt to increase biogas production for utilization in combined heat and power systems, fed into natural gas pipelines or as a vehicle fuel. This study evaluated the impact and benefits of Ni/Co and olivine addition to the digester at mesophilic temperatures. These additions supplement previously reported research in which iron-rich olivine (MgSiO4) was added to sequester CO2 in-situ during batch AD of sludge. Trace element addition has been shown to stimulate and stabilize biogas production and have amore » synergistic effect on the mineral carbonation process. AD with 5% w/v olivine and 1.5 mg/L Ni/Co addition had a 17.3% increase in methane volume, a 6% increase in initial exponential methane production rate and a 56% increase in methane yield (mL CH4/g CODdegraded) compared to the control due to synergistic trace element and olivine addition while maintaining 17.7% CO2 sequestration from olivine addition. Both first-order kinetic modeling and response surface methodology modeling confirmed the combined benefit of the trace elements and olivine addition. These results were significantly higher than previously reported results with olivine addition alone [1].« less

An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

Computational modelling of biochemical systems based on top-down and bottom-up approaches has been well studied over the last decade. In this research, after illustrating how to generate atomic components by a set of given reactants and two user pre-defined component patterns, we propose an integrative top-down and bottom-up modelling approach for stepwise qualitative exploration of interactions among reactants in biochemical systems. Evolution strategy is applied to the top-down modelling approach to compose models, and simulated annealing is employed in the bottom-up modelling approach to explore potential interactions based on models constructed from the top-down modelling process. Both the top-down and bottom-up approaches support stepwise modular addition or subtraction for the model evolution. Experimental results indicate that our modelling approach is feasible to learn the relationships among biochemical reactants qualitatively. In addition, hidden reactants of the target biochemical system can be obtained by generating complex reactants in corresponding composed models. Moreover, qualitatively learned models with inferred reactants and alternative topologies can be used for further web-lab experimental investigations by biologists of interest, which may result in a better understanding of the system.

Estimating the Additional Greenhouse Gas Emissions in Korea: Focused on Demolition of Asbestos Containing Materials in Building

PubMed Central

Kim, Young-Chan; Hong, Won-Hwa; Zhang, Yuan-Long; Son, Byeung-Hun; Seo, Youn-Kyu; Choi, Jun-Ho

2016-01-01

When asbestos containing materials (ACM) must be removed from the building before demolition, additional greenhouse gas (GHG) emissions are generated. However, precedent studies have not considered the removal of ACM from the building. The present study aimed to develop a model for estimating GHG emissions created by the ACM removal processes, specifically the removal of asbestos cement slates (ACS). The second objective was to use the new model to predict the total GHG emission produced by ACM removal in the entire country of Korea. First, an input-equipment inventory was established for each step of the ACS removal process. Second, an energy consumption database for each equipment type was established. Third, the total GHG emission contributed by each step of the process was calculated. The GHG emissions generated from the 1,142,688 ACS-containing buildings in Korea was estimated to total 23,778 tonCO2eq to 132,141 tonCO2eq. This study was meaningful in that the emissions generated by ACS removal have not been studied before. Furthermore, the study deals with additional problems that can be triggered by the presence of asbestos in building materials. The method provided in this study is expected to contribute greatly to the calculation of GHG emissions caused by ACM worldwide. PMID:27626433

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

NASA Technical Reports Server (NTRS)

De Boer, G.; Shupe, M.D.; Caldwell, P.M.; Bauer, Susanne E.; Persson, O.; Boyle, J.S.; Kelley, M.; Klein, S.A.; Tjernstrom, M.

2014-01-01

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles.

PubMed

Sizochenko, Natalia; Rasulev, Bakhtiyor; Gajewicz, Agnieszka; Kuz'min, Victor; Puzyn, Tomasz; Leszczynski, Jerzy

2014-11-21

Many metal oxide nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of metal oxide nanoparticles' toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of nanoparticles' structure is presented. For description of the supramolecular structure of nanoparticles the "liquid drop" model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand-metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied metal oxide nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and metal-ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.

A statistical model for monitoring shell disease in inshore lobster fisheries: A case study in Long Island Sound

PubMed Central

Chen, Yong

2017-01-01

The expansion of shell disease is an emerging threat to the inshore lobster fisheries in the northeastern United States. The development of models to improve the efficiency and precision of existing monitoring programs is advocated as an important step in mitigating its harmful effects. The objective of this study is to construct a statistical model that could enhance the existing monitoring effort through (1) identification of potential disease-associated abiotic and biotic factors, and (2) estimation of spatial variation in disease prevalence in the lobster fishery. A delta-generalized additive modeling (GAM) approach was applied using bottom trawl survey data collected from 2001–2013 in Long Island Sound, a tidal estuary between New York and Connecticut states. Spatial distribution of shell disease prevalence was found to be strongly influenced by the interactive effects of latitude and longitude, possibly indicative of a geographic origin of shell disease. Bottom temperature, bottom salinity, and depth were also important factors affecting the spatial variability in shell disease prevalence. The delta-GAM projected high disease prevalence in non-surveyed locations. Additionally, a potential spatial discrepancy was found between modeled disease hotspots and survey-based gravity centers of disease prevalence. This study provides a modeling framework to enhance research, monitoring and management of emerging and continuing marine disease threats. PMID:28196150

A Matter of the Heart: The African Clawed Frog Xenopus as a Model for Studying Vertebrate Cardiogenesis and Congenital Heart Defects

PubMed Central

Hempel, Annemarie; Kühl, Michael

2016-01-01

The African clawed frog, Xenopus, is a valuable non-mammalian model organism to investigate vertebrate heart development and to explore the underlying molecular mechanisms of human congenital heart defects (CHDs). In this review, we outline the similarities between Xenopus and mammalian cardiogenesis, and provide an overview of well-studied cardiac genes in Xenopus, which have been associated with congenital heart conditions. Additionally, we highlight advantages of modeling candidate genes derived from genome wide association studies (GWAS) in Xenopus and discuss commonly used techniques. PMID:29367567

Comparing models of the combined-stimulation advantage for speech recognition.

PubMed

Micheyl, Christophe; Oxenham, Andrew J

2012-05-01

The "combined-stimulation advantage" refers to an improvement in speech recognition when cochlear-implant or vocoded stimulation is supplemented by low-frequency acoustic information. Previous studies have been interpreted as evidence for "super-additive" or "synergistic" effects in the combination of low-frequency and electric or vocoded speech information by human listeners. However, this conclusion was based on predictions of performance obtained using a suboptimal high-threshold model of information combination. The present study shows that a different model, based on Gaussian signal detection theory, can predict surprisingly large combined-stimulation advantages, even when performance with either information source alone is close to chance, without involving any synergistic interaction. A reanalysis of published data using this model reveals that previous results, which have been interpreted as evidence for super-additive effects in perception of combined speech stimuli, are actually consistent with a more parsimonious explanation, according to which the combined-stimulation advantage reflects an optimal combination of two independent sources of information. The present results do not rule out the possible existence of synergistic effects in combined stimulation; however, they emphasize the possibility that the combined-stimulation advantages observed in some studies can be explained simply by non-interactive combination of two information sources.

The contribution of illness perceptions and metacognitive beliefs to anxiety and depression in adults with diabetes.

PubMed

Purewal, Rebecca; Fisher, Peter L

2018-02-01

Anxiety and depression are highly prevalent in people with diabetes (PwD). The most widely used psychological model to explain anxiety and depression in PwD is the Common-Sense Model, which gives a central role to illness perceptions. The Self-Regulatory Executive Function (S-REF) model proposes metacognitive beliefs are key to understanding the development and maintenance of emotional disorders. To test the potential utility of the S-REF model in PwD, the study explored if metacognitive beliefs explained additional variance in anxiety and depression after controlling for demographic and illness perceptions. 614 adults with either Type 1 (n = 335) or Type 2 (n = 279) diabetes participated in a cross sectional online survey. All participants completed questionnaires on anxiety, depression, illness perceptions and metacognitive beliefs. Regression analyses showed that metacognitive beliefs were associated with anxiety and depression in PwD and explained additional variance in both anxiety and depression after controlling for demographics and illness perceptions. This is the first study to demonstrate that metacognitive beliefs are associated with anxiety and depression in PwD. The clinical implications of the study are illustrated. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

A second-order closure analysis of turbulent diffusion flames. [combustion physics

NASA Technical Reports Server (NTRS)

Varma, A. K.; Fishburne, E. S.; Beddini, R. A.

1977-01-01

A complete second-order closure computer program for the investigation of compressible, turbulent, reacting shear layers was developed. The equations for the means and the second order correlations were derived from the time-averaged Navier-Stokes equations and contain third order and higher order correlations, which have to be modeled in terms of the lower-order correlations to close the system of equations. In addition to fluid mechanical turbulence models and parameters used in previous studies of a variety of incompressible and compressible shear flows, a number of additional scalar correlations were modeled for chemically reacting flows, and a typical eddy model developed for the joint probability density function for all the scalars. The program which is capable of handling multi-species, multistep chemical reactions, was used to calculate nonreacting and reacting flows in a hydrogen-air diffusion flame.

Sport commitment among competitive female athletes: test of an expanded model.

PubMed

Weiss, Windee M; Weiss, Maureen R; Amorose, Anthony J

2010-02-01

In the present study, we examined an expanded model of sport commitment by adding two determinants (perceived costs and perceived competence) and behavioural commitment as a consequence of psychological commitment, as well as identifying psychological commitment as a mediator of relationships between determinants and behavioural commitment. Competitive female gymnasts (N = 304, age 8-18 years) completed relevant measures while coaches rated each gymnast's training behaviours as an indicator of behavioural commitment. Path analysis revealed that the best fitting model was one in which original determinants (enjoyment, involvement opportunities, investments, attractive alternatives) and an added determinant (perceived costs) predicted psychological commitment, in addition to investments and perceived costs directly predicting behavioural commitment. These results provide further, but partial, support for the sport commitment model and also suggest that additional determinants and behavioural consequences be considered in future research.

Stationarity is undead: Uncertainty dominates the distribution of extremes

NASA Astrophysics Data System (ADS)

Serinaldi, Francesco; Kilsby, Chris G.

2015-03-01

The increasing effort to develop and apply nonstationary models in hydrologic frequency analyses under changing environmental conditions can be frustrated when the additional uncertainty related to the model complexity is accounted for along with the sampling uncertainty. In order to show the practical implications and possible problems of using nonstationary models and provide critical guidelines, in this study we review the main tools developed in this field (such as nonstationary distribution functions, return periods, and risk of failure) highlighting advantages and disadvantages. The discussion is supported by three case studies that revise three illustrative examples reported in the scientific and technical literature referring to the Little Sugar Creek (at Charlotte, North Carolina), Red River of the North (North Dakota/Minnesota), and the Assunpink Creek (at Trenton, New Jersey). The uncertainty of the results is assessed by complementing point estimates with confidence intervals (CIs) and emphasizing critical aspects such as the subjectivity affecting the choice of the models' structure. Our results show that (1) nonstationary frequency analyses should not only be based on at-site time series but require additional information and detailed exploratory data analyses (EDA); (2) as nonstationary models imply that the time-varying model structure holds true for the entire future design life period, an appropriate modeling strategy requires that EDA identifies a well-defined deterministic mechanism leading the examined process; (3) when the model structure cannot be inferred in a deductive manner and nonstationary models are fitted by inductive inference, model structure introduces an additional source of uncertainty so that the resulting nonstationary models can provide no practical enhancement of the credibility and accuracy of the predicted extreme quantiles, whereas possible model misspecification can easily lead to physically inconsistent results; (4) when the model structure is uncertain, stationary models and a suitable assessment of the uncertainty accounting for possible temporal persistence should be retained as more theoretically coherent and reliable options for practical applications in real-world design and management problems; (5) a clear understanding of the actual probabilistic meaning of stationary and nonstationary return periods and risk of failure is required for a correct risk assessment and communication.

Initialization and Setup of the Coastal Model Test Bed: STWAVE

DTIC Science & Technology

2017-01-01

Laboratory (CHL) Field Research Facility (FRF) in Duck , NC. The improved evaluation methodology will promote rapid enhancement of model capability and focus...Blanton 2008) study . This regional digital elevation model (DEM), with a cell size of 10 m, was generated from numerous datasets collected at different...INFORMATION: For additional information, contact Spicer Bak, Coastal Observation and Analysis Branch, Coastal and Hydraulics Laboratory, 1261 Duck Road

Reciprocal Peer Assessment as a Learning Tool for Secondary School Students in Modeling-Based Learning

ERIC Educational Resources Information Center

Tsivitanidou, Olia E.; Constantinou, Costas P.; Labudde, Peter; Rönnebeck, Silke; Ropohl, Mathias

2018-01-01

The aim of this study was to investigate how reciprocal peer assessment in modeling-based learning can serve as a learning tool for secondary school learners in a physics course. The participants were 22 upper secondary school students from a gymnasium in Switzerland. They were asked to model additive and subtractive color mixing in groups of two,…

Air-water analogy and the study of hydraulic models

NASA Technical Reports Server (NTRS)

Supino, Giulio

1953-01-01

The author first sets forth some observations about the theory of models. Then he established certain general criteria for the construction of dynamically similar models in water and in air, through reference to the perfect fluid equations and to the ones pertaining to viscous flow. It is, in addition, pointed out that there are more cases in which the analogy is possible than is commonly supposed.

The intersection of aggregate-level lead exposure and crime.

PubMed

Boutwell, Brian B; Nelson, Erik J; Emo, Brett; Vaughn, Michael G; Schootman, Mario; Rosenfeld, Richard; Lewis, Roger

2016-07-01

Childhood lead exposure has been associated with criminal behavior later in life. The current study aimed to analyze the association between elevated blood lead levels (n=59,645) and crime occurrence (n=90,433) across census tracts within St. Louis, Missouri. Longitudinal ecological study. Saint Louis, Missouri. Blood lead levels. Violent, Non-violent, and total crime at the census tract level. Spatial statistical models were used to account for the spatial autocorrelation of the data. Greater lead exposure at the census-tract level was associated with increased violent, non-violent, and total crime. In addition, we examined whether non-additive effects existed in the data by testing for an interaction between lead exposure and concentrated disadvantage. Some evidence of a negative interaction emerged, however, it failed to reach traditional levels of statistical significance (supplementary models, however, revealed a similar negative interaction that was significant). More precise measurements of lead exposure in the aggregate, produced additional evidence that lead is a potent predictor of criminal outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Combat Wound Initiative program.

PubMed

Stojadinovic, Alexander; Elster, Eric; Potter, Benjamin K; Davis, Thomas A; Tadaki, Doug K; Brown, Trevor S; Ahlers, Stephen; Attinger, Christopher E; Andersen, Romney C; Burris, David; Centeno, Jose; Champion, Hunter; Crumbley, David R; Denobile, John; Duga, Michael; Dunne, James R; Eberhardt, John; Ennis, William J; Forsberg, Jonathan A; Hawksworth, Jason; Helling, Thomas S; Lazarus, Gerald S; Milner, Stephen M; Mullick, Florabel G; Owner, Christopher R; Pasquina, Paul F; Patel, Chirag R; Peoples, George E; Nissan, Aviram; Ring, Michael; Sandberg, Glenn D; Schaden, Wolfgang; Schultz, Gregory S; Scofield, Tom; Shawen, Scott B; Sheppard, Forest R; Stannard, James P; Weina, Peter J; Zenilman, Jonathan M

2010-07-01

The Combat Wound Initiative (CWI) program is a collaborative, multidisciplinary, and interservice public-private partnership that provides personalized, state-of-the-art, and complex wound care via targeted clinical and translational research. The CWI uses a bench-to-bedside approach to translational research, including the rapid development of a human extracorporeal shock wave therapy (ESWT) study in complex wounds after establishing the potential efficacy, biologic mechanisms, and safety of this treatment modality in a murine model. Additional clinical trials include the prospective use of clinical data, serum and wound biomarkers, and wound gene expression profiles to predict wound healing/failure and additional clinical patient outcomes following combat-related trauma. These clinical research data are analyzed using machine-based learning algorithms to develop predictive treatment models to guide clinical decision-making. Future CWI directions include additional clinical trials and study centers and the refinement and deployment of our genetically driven, personalized medicine initiative to provide patient-specific care across multiple medical disciplines, with an emphasis on combat casualty care.

[Leisure activities, resilience and mental stress in adolescents].

PubMed

Karpinski, Norbert; Popal, Narges; Plück, Julia; Petermann, Franz; Lehmkuhl, Gerd

2017-01-01

To date, the factors contributing to emergence of resilience in different stages of adolescence have yet to be sufficiently examined. This study looks at the influence of extracurricular activities on resilience. The sample consists of 413 adolescents (f = 14.8) reporting personal problems (mood, concentration problems, behavior). The effect of extracurricular activities on resilience (gathered by the RS25) was analyzed by linear regression models. Predictor variables in these models were extracurricular activities (sport, hobbies, club memberships, household duties) and the subscales of the SDQ (Strengths and Difficulties Questionnaire). Because of the lack of homoscedasticity, two different regression models (model A: Realschule and Grammar School. Model B: Hauptschule) were specified. The explained variance of both models (model A: R = .516; model B: R = .643) is satisfactory. In both models “prosocial behavior” (SDQ) turns out to be a significant positive predictor for resilience (model A: b = 2.815; model B; b = 3.577) and emotional symptoms (model A: b = -1.697; model B: b = -2.596) are significant negative predictors for resilience. In addition, model A presents significant positive influences of sport (b = 16,314) and significant negative influences of “hyperactivity” (SDQ). In contrast, in model B “club memberships” (b = 15.775) and” peer relationship problems” (b = 1.508) are additional positive predictors. The results of the study demonstrate the important role of prosocial behavior and emotional competence in the manifestation of resilience. The effect of extracurricular activities proves to depend on the social environment (type of school). Thus, these results could form the basis for further more specific developmental programs.

Ecotoxicological assessment of oil-based paint using three-dimensional multi-species bio-testing model: pre- and post-bioremediation analysis.

PubMed

Phulpoto, Anwar Hussain; Qazi, Muneer Ahmed; Haq, Ihsan Ul; Phul, Abdul Rahman; Ahmed, Safia; Kanhar, Nisar Ahmed

2018-06-01

The present study validates the oil-based paint bioremediation potential of Bacillus subtilis NAP1 for ecotoxicological assessment using a three-dimensional multi-species bio-testing model. The model included bioassays to determine phytotoxic effect, cytotoxic effect, and antimicrobial effect of oil-based paint. Additionally, the antioxidant activity of pre- and post-bioremediation samples was also detected to confirm its detoxification. Although, the pre-bioremediation samples of oil-based paint displayed significant toxicity against all the life forms. However, post-bioremediation, the cytotoxic effect against Artemia salina revealed substantial detoxification of oil-based paint with LD 50 of 121 μl ml -1 (without glucose) and > 400 μl ml -1 (with glucose). Similarly, the reduction in toxicity against Raphanus raphanistrum seeds germination (%FG = 98 to 100%) was also evident of successful detoxification under experimental conditions. Moreover, the toxicity against test bacterial strains and fungal strains was completely removed after bioremediation. In addition, the post-bioremediation samples showed reduced antioxidant activities (% scavenging = 23.5 ± 0.35 and 28.9 ± 2.7) without and with glucose, respectively. Convincingly, the present multi-species bio-testing model in addition to antioxidant studies could be suggested as a validation tool for bioremediation experiments, especially for middle and low-income countries. Graphical abstract ᅟ.

Learning-based saliency model with depth information.

PubMed

Ma, Chih-Yao; Hang, Hsueh-Ming

2015-01-01

Most previous studies on visual saliency focused on two-dimensional (2D) scenes. Due to the rapidly growing three-dimensional (3D) video applications, it is very desirable to know how depth information affects human visual attention. In this study, we first conducted eye-fixation experiments on 3D images. Our fixation data set comprises 475 3D images and 16 subjects. We used a Tobii TX300 eye tracker (Tobii, Stockholm, Sweden) to track the eye movement of each subject. In addition, this database contains 475 computed depth maps. Due to the scarcity of public-domain 3D fixation data, this data set should be useful to the 3D visual attention research community. Then, a learning-based visual attention model was designed to predict human attention. In addition to the popular 2D features, we included the depth map and its derived features. The results indicate that the extra depth information can enhance the saliency estimation accuracy specifically for close-up objects hidden in a complex-texture background. In addition, we examined the effectiveness of various low-, mid-, and high-level features on saliency prediction. Compared with both 2D and 3D state-of-the-art saliency estimation models, our methods show better performance on the 3D test images. The eye-tracking database and the MATLAB source codes for the proposed saliency model and evaluation methods are available on our website.

Insecure attachment style as a vulnerability factor for depression: recent findings in a community-based study of Malay single and married mothers.

PubMed

Abdul Kadir, Nor Ba'yah; Bifulco, Antonia

2013-12-30

The role of marital breakdown in women's mental health is of key concern in Malaysia and internationally. A cross-sectional questionnaire study of married and separated/divorced and widowed women examined insecure attachment style as an associated risk factor for depression among 1002 mothers in an urban community in Malaysia. A previous report replicated a UK-based vulnerability-provoking agent model of depression involving negative evaluation of self (NES) and negative elements in close relationships (NECRs) interacting with severe life events to model depression. This article reports on the additional contribution of insecure attachment style to the model using the Vulnerable Attachment Style Questionnaire (VASQ). The results showed that VASQ scores were highly correlated with NES, NECR and depression. A multiple regression analysis of depression with backward elimination found that VASQ scores had a significant additional effect. Group comparisons showed different risk patterns for single and married mothers. NES was the strongest risk factor for both groups, with the 'anxious style' subset of the VASQ being the best additional predictor for married mothers and the total VASQ score (general attachment insecurity) for single mothers. The findings indicate that attachment insecurity adds to a psychosocial vulnerability model of depression among mothers cross-culturally and is important in understanding and identifying risk. © 2013 Elsevier Ireland Ltd. All rights reserved.

A dielectric model of self-assembled monolayer interfaces by capacitive spectroscopy.

PubMed

Góes, Márcio S; Rahman, Habibur; Ryall, Joshua; Davis, Jason J; Bueno, Paulo R

2012-06-26

The presence of self-assembled monolayers at an electrode introduces capacitance and resistance contributions that can profoundly affect subsequently observed electronic characteristics. Despite the impact of this on any voltammetry, these contributions are not directly resolvable with any clarity by standard electrochemical means. A capacitive analysis of such interfaces (by capacitance spectroscopy), introduced here, enables a clean mapping of these features and additionally presents a means of studying layer polarizability and Cole-Cole relaxation effects. The resolved resistive term contributes directly to an intrinsic monolayer uncompensated resistance that has a linear dependence on the layer thickness. The dielectric model proposed is fully aligned with the classic Helmholtz plate capacitor model and additionally explains the inherently associated resistive features of molecular films.

Statistical inference for the additive hazards model under outcome-dependent sampling.

PubMed

Yu, Jichang; Liu, Yanyan; Sandler, Dale P; Zhou, Haibo

2015-09-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer.

Statistical inference for the additive hazards model under outcome-dependent sampling

PubMed Central

Yu, Jichang; Liu, Yanyan; Sandler, Dale P.; Zhou, Haibo

2015-01-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer. PMID:26379363

Laboratory evaluation of friction loss and compactability of asphalt mixtures.

DOT National Transportation Integrated Search

2012-04-01

This study aimed to develop prediction models for friction loss and laboratory compaction of asphalt : mixtures. In addition, the study evaluated the effect of compaction level and compaction method of skid : resistance and the internal structure of ...

A green vehicle routing problem with customer satisfaction criteria

NASA Astrophysics Data System (ADS)

Afshar-Bakeshloo, M.; Mehrabi, A.; Safari, H.; Maleki, M.; Jolai, F.

2016-12-01

This paper develops an MILP model, named Satisfactory-Green Vehicle Routing Problem. It consists of routing a heterogeneous fleet of vehicles in order to serve a set of customers within predefined time windows. In this model in addition to the traditional objective of the VRP, both the pollution and customers' satisfaction have been taken into account. Meanwhile, the introduced model prepares an effective dashboard for decision-makers that determines appropriate routes, the best mixed fleet, speed and idle time of vehicles. Additionally, some new factors evaluate the greening of each decision based on three criteria. This model applies piecewise linear functions (PLFs) to linearize a nonlinear fuzzy interval for incorporating customers' satisfaction into other linear objectives. We have presented a mixed integer linear programming formulation for the S-GVRP. This model enriches managerial insights by providing trade-offs between customers' satisfaction, total costs and emission levels. Finally, we have provided a numerical study for showing the applicability of the model.

Animal Models for Periodontal Disease

PubMed Central

Oz, Helieh S.; Puleo, David A.

2011-01-01

Animal models and cell cultures have contributed new knowledge in biological sciences, including periodontology. Although cultured cells can be used to study physiological processes that occur during the pathogenesis of periodontitis, the complex host response fundamentally responsible for this disease cannot be reproduced in vitro. Among the animal kingdom, rodents, rabbits, pigs, dogs, and nonhuman primates have been used to model human periodontitis, each with advantages and disadvantages. Periodontitis commonly has been induced by placing a bacterial plaque retentive ligature in the gingival sulcus around the molar teeth. In addition, alveolar bone loss has been induced by inoculation or injection of human oral bacteria (e.g., Porphyromonas gingivalis) in different animal models. While animal models have provided a wide range of important data, it is sometimes difficult to determine whether the findings are applicable to humans. In addition, variability in host responses to bacterial infection among individuals contributes significantly to the expression of periodontal diseases. A practical and highly reproducible model that truly mimics the natural pathogenesis of human periodontal disease has yet to be developed. PMID:21331345

A Bayesian model for estimating population means using a link-tracing sampling design.

PubMed

St Clair, Katherine; O'Connell, Daniel

2012-03-01

Link-tracing sampling designs can be used to study human populations that contain "hidden" groups who tend to be linked together by a common social trait. These links can be used to increase the sampling intensity of a hidden domain by tracing links from individuals selected in an initial wave of sampling to additional domain members. Chow and Thompson (2003, Survey Methodology 29, 197-205) derived a Bayesian model to estimate the size or proportion of individuals in the hidden population for certain link-tracing designs. We propose an addition to their model that will allow for the modeling of a quantitative response. We assess properties of our model using a constructed population and a real population of at-risk individuals, both of which contain two domains of hidden and nonhidden individuals. Our results show that our model can produce good point and interval estimates of the population mean and domain means when our population assumptions are satisfied. © 2011, The International Biometric Society.

A penalized framework for distributed lag non-linear models.

PubMed

Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G

2017-09-01

Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Microscopic aspects of the effect of friction reducers at the lubrication limit. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Mansot, J. L.

1984-01-01

An attempt is made to analytically model the physicochemical properties of lubricants and their capacity to reduce friction. A technique of frozen fracturing of the lubricants was employed to study the dispersion of additives throughout a lubricant. Adsorption was observed at the liquid-solid interface, which was the region where the solid and lubricant met, and the molecular dispersion of the additive enhanced the effectiveness of the lubricant. The electrically conductive characteristics of the lubricant at the friction interface indicated the presence of tunneling effects. The Bethe model was used to examine the relationship between the coefficient of friction and the variation of interface thickness. The electron transport permitted an inelastic tunnel electron spectroscopic investigation of the molecular transformations undergone by the additive during friction episodes.

Class Evolution Tree: A Graphical Tool to Support Decisions on the Number of Classes in Exploratory Categorical Latent Variable Modeling for Rehabilitation Research

ERIC Educational Resources Information Center

Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

2011-01-01

The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…

KIAA0319 gene polymorphisms are associated with developmental dyslexia in Chinese Uyghur children

PubMed Central

Zhao, Hua; Chen, Yun; Zhang, Bao-ping; Zuo, Peng-xiang

2016-01-01

The gene KIAA0319 has been reported to be associated with developmental dyslexia (DD) in previous studies, although the results have not always been consistent. However, few studies have been conducted in Uyghur populations. In the present study, we aimed to investigate the association of KIAA0319 polymorphisms and DD in individuals of Uyghurian descent. We used a custom-by-design 48-Plex SNPscan Kit to genotype 18 single-nucleotide polymorphisms (SNPs) of KIAA0319 in a group of 196 children with dyslexia and 196 controls of Uyghur descent aged 8–12 years. As a result, 7 SNPs (Pmin=0.001) of KIAA0319 had nominal significant differences between the cases and controls under specific genotypic models. The two SNPs rs6935076 (P=0.020 under dominant model; P=0.028 under additive model) and rs3756821 (P=0.021 under additive model) remained significantly associated with dyslexia after Bonferroni correction. Linkage disequilibrium analysis showed three blocks within KIAA0319, and only a 10-SNP haplotype in block 3 was present at significantly different frequencies in the dyslexic children and controls. This study indicated that genetic polymorphisms of KIAA0319 are associated with an increased risk of DD in the Uyghur population. PMID:27098879

Markov Mixed Effects Modeling Using Electronic Adherence Monitoring Records Identifies Influential Covariates to HIV Preexposure Prophylaxis.

PubMed

Madrasi, Kumpal; Chaturvedula, Ayyappa; Haberer, Jessica E; Sale, Mark; Fossler, Michael J; Bangsberg, David; Baeten, Jared M; Celum, Connie; Hendrix, Craig W

2017-05-01

Adherence is a major factor in the effectiveness of preexposure prophylaxis (PrEP) for HIV prevention. Modeling patterns of adherence helps to identify influential covariates of different types of adherence as well as to enable clinical trial simulation so that appropriate interventions can be developed. We developed a Markov mixed-effects model to understand the covariates influencing adherence patterns to daily oral PrEP. Electronic adherence records (date and time of medication bottle cap opening) from the Partners PrEP ancillary adherence study with a total of 1147 subjects were used. This study included once-daily dosing regimens of placebo, oral tenofovir disoproxil fumarate (TDF), and TDF in combination with emtricitabine (FTC), administered to HIV-uninfected members of serodiscordant couples. One-coin and first- to third-order Markov models were fit to the data using NONMEM ® 7.2. Model selection criteria included objective function value (OFV), Akaike information criterion (AIC), visual predictive checks, and posterior predictive checks. Covariates were included based on forward addition (α = 0.05) and backward elimination (α = 0.001). Markov models better described the data than 1-coin models. A third-order Markov model gave the lowest OFV and AIC, but the simpler first-order model was used for covariate model building because no additional benefit on prediction of target measures was observed for higher-order models. Female sex and older age had a positive impact on adherence, whereas Sundays, sexual abstinence, and sex with a partner other than the study partner had a negative impact on adherence. Our findings suggest adherence interventions should consider the role of these factors. © 2016, The American College of Clinical Pharmacology.

A comparison of traditional anti-inflammation and anti-infection medicinal plants with current evidence from biomedical research: Results from a regional study

PubMed Central

Vieira, A.

2010-01-01

Background: In relation to pharmacognosy, an objective of many ethnobotanical studies is to identify plant species to be further investigated, for example, tested in disease models related to the ethnomedicinal application. To further warrant such testing, research evidence for medicinal applications of these plants (or of their major phytochemical constituents and metabolic derivatives) is typically analyzed in biomedical databases. Methods: As a model of this process, the current report presents novel information regarding traditional anti-inflammation and anti-infection medicinal plant use. This information was obtained from an interview-based ethnobotanical study; and was compared with current biomedical evidence using the Medline® database. Results: Of the 8 anti-infection plant species identified in the ethnobotanical study, 7 have related activities reported in the database; and of the 6 anti-inflammation plants, 4 have related activities in the database. Conclusion: Based on novel and complimentary results from the ethnobotanical and biomedical database analyses, it is suggested that some of these plants warrant additional investigation of potential anti-inflammatory or anti-infection activities in related disease models, and also additional studies in other population groups. PMID:21589754

Strange Quark Matter Status and Prospects

NASA Technical Reports Server (NTRS)

Sandweiss, J.

2004-01-01

The existence of quark states with more than three quarks is allowed in QCD. The stability of such quark matter states has been studied with lattice QCD and phenomenological bag models, but is not well constrained by theory. The addition of strange quarks to the system allows the quarks to be in lower energy states despite the additional mass penalty. There is additional stability from reduced Coulomb repulsion. SQM is expected to have a low Z/A. Stable or metastable massive multiquark states contain u, d, and s quarks.

Synthesis, characterization and study of sorption parameters of multi-walled carbon nanotubes/chitosan nanocomposite for the removal of picric acid from aqueous solutions.

PubMed

Khakpour, Roghayeh; Tahermansouri, Hasan

2018-04-01

The modification of carboxylated multi-wall carbon nanotubes (MWCNT-COOH) with chitosan (Chi) has been investigated to prepare a nanocomposite material (MWCNT-Chi) for the removal of picric acid from aqueous solutions. Materials were characterized by FT-IR, TGA, DTG, FESEM, EDX, BET and zeta potential. Batch experiments such as solution pH, dosage of adsorbents, contact time, concentration of the picric acid and temperature were achieved to study sorption process. Kinetic studies were well described by pseudo-second-order kinetic model for both adsorbents. The six isotherm models: Langmuir (four linear forms), Freundlich, Tempkin, Halsey, Harkins-Jura and Dubinin-Radushkevich models were applied to determine the characteristic parameters of the adsorption process. Isotherm studies showed that the Langmuir isotherm for MWCNT-Chi and Freundlich and Halsey models for both adsorbents were found to best represent the measured sorption data. In addition, the results of Dubinin-Radushkevich model confirmed the physical adsorption. Negative ΔG° values for MWCNT-Chi and positive ones for MWCNT-COOH indicated the nature of spontaneous and unspontaneous, respectively for adsorption process in the range of the studied concentrations. In addition, picric acid molecules can be desorbed from MWCNT-Chi up to 90% at pH = 9 and that the consumed MWCNT-Chi could be reutilized up to 5th cycle of regeneration. Copyright © 2017 Elsevier B.V. All rights reserved.

Hierarchical additive modeling of nonlinear association with spatial correlations--an application to relate alcohol outlet density and neighborhood assault rates.

PubMed

Yu, Qingzhao; Li, Bin; Scribner, Richard Allen

2009-06-30

Previous studies have suggested a link between alcohol outlets and assaults. In this paper, we explore the effects of alcohol availability on assaults at the census tract level over time. In addition, we use a natural experiment to check whether a sudden loss of alcohol outlets is associated with deeper decreasing in assault violence. Several features of the data raise statistical challenges: (1) the association between covariates (for example, the alcohol outlet density of each census tract) and the assault rates may be complex and therefore cannot be described using a linear model without covariates transformation, (2) the covariates may be highly correlated with each other, (3) there are a number of observations that have missing inputs, and (4) there is spatial association in assault rates at the census tract level. We propose a hierarchical additive model, where the nonlinear correlations and the complex interaction effects are modeled using the multiple additive regression trees and the residual spatial association in the assault rates that cannot be explained in the model are smoothed using a conditional autoregressive (CAR) method. We develop a two-stage algorithm that connects the nonparametric trees with CAR to look for important covariates associated with the assault rates, while taking into account the spatial association of assault rates in adjacent census tracts. The proposed method is applied to the Los Angeles assault data (1990-1999). To assess the efficiency of the method, the results are compared with those obtained from a hierarchical linear model. Copyright (c) 2009 John Wiley & Sons, Ltd.

General personality and psychopathology in referred and nonreferred children and adolescents: an investigation of continuity, pathoplasty, and complication models.

PubMed

De Bolle, Marleen; Beyers, Wim; De Clercq, Barbara; De Fruyt, Filip

2012-11-01

This study investigated the continuity, pathoplasty, and complication models as plausible explanations for personality-psychopathology relations in a combined sample of community (n = 571) and referred (n = 146) children and adolescents. Multivariate structural equation modeling was used to examine the structural relations between latent personality and psychopathology change across a 2-year period. Item response theory models were fitted as an additional test of the continuity hypothesis. Even after correcting for item overlap, the results provided strong support for the continuity model, demonstrating that personality and psychopathology displayed dynamic change patterns across time. Item response theory models further supported the continuity conceptualization for understanding the association between internalizing problems and emotional stability and extraversion as well as between externalizing problems and benevolence and conscientiousness. In addition to the continuity model, particular personality and psychopathology combinations provided evidence for the pathoplasty and complication models. The theoretical and practical implications of these results are discussed, and suggestions for future research are provided. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

The Impact of Microphysical Schemes on Intensity and Track of Hurricane

NASA Technical Reports Server (NTRS)

Tao, W. K.; Shi, J. J.; Chen, S. S.; Lang, S.; Lin, P.; Hong, S. Y.; Peters-Lidard, C.; Hou, A.

2010-01-01

During the past decade, both research and operational numerical weather prediction models [e.g. Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. The WRF is a next-generation meso-scale forecast model and assimilation system that has incorporated a modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. The WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At Goddard, four different cloud microphysics schemes (warm rain only, two-class of ice, two three-class of ice with either graupel or hail) are implemented into the WRF. The performances of these schemes have been compared to those from other WRF microphysics scheme options for an Atlantic hurricane case. In addition, a brief review and comparison on the previous modeling studies on the impact of microphysics schemes and microphysical processes on intensity and track of hurricane will be presented. Generally, almost all modeling studies found that the microphysics schemes did not have major impacts on track forecast, but did have more effect on the intensity. All modeling studies found that the simulated hurricane has rapid deepening and/or intensification for the warm rain-only case. It is because all hydrometeors were very large raindrops, and they fell out quickly at and near the eye-wall region. This would hydrostatically produce the lowest pressure. In addition, these modeling studies suggested that the simulated hurricane becomes unrealistically strong by removing the evaporative cooling of cloud droplets and melting of ice particles. This is due to the much weaker downdraft simulated. However, there are many differences between different modeling studies and these differences were identified and discussed.

Modeling the effects of strain profiles and defects on precessional magnetic switching in multiferroic heterostructures

NASA Astrophysics Data System (ADS)

Chavez, Andres C.; Kundu, Auni A.; Lynch, Christopher S.; Carman, Gregory P.

2018-03-01

Strain-mediated multiferroic heterostructures relying on fast 180° precessional magnetic switching have been proposed as a pathway for energy efficient and high density memory/logic devices. However, proper device performance requires precisely timed high frequency ( GHz) voltage pulses dependent on the magnetization dynamics of the structure. In turn, the dynamic response of the device is greatly influenced by the device geometry, strain amplitude, and strain rate. Hence, we study the effects of increasing the voltage amplitude and application rate on the in-plane magnetization dynamics of a single-domain CoFeB ellipse (100 nm x 80 nm x 6 nm) on a 500 nm thick PZT substrate in addition to studying defects in the geometry. Both a coupled micromagnetics, electrostatics and elastodynamics finite element model and a conventional micromagnetics software was used to study the strain-induced magnetic response of the CoFeB ellipse. Both models predict increased 90° magnetic reorientation speed with increased strain amplitude and rate. However, the fully-coupled model predicts slower reorientation and incoherency in comparison to the uncoupled model. This occurs because the fully-coupled model can capture the expected strain gradients of a fabricated device while the micromagnetics model can only represent uniform strain states. Additional studies which introduce geometric defects result in faster precessional motion under the same strain amplitude and rate. This is attributed to localized changes in the magnetization that influence neighboring regions via exchange and demagnetization effects. The results of these studies can help design better devices that will be less sensitive to defects and voltage applications for future strain-mediated multiferroic devices.

Influence of backup bearings and support structure dynamics on the behavior of rotors with active supports

NASA Technical Reports Server (NTRS)

Flowers, George T.

1995-01-01

This semiannual status report lists specific accomplishments made on the research of the influence of backup bearings and support structure dynamics on the behavior of rotors with active supports. Papers have been presented representing work done on the T-501 engine model; an experimental/simulation study of auxiliary bearing rotordynamics; and a description of a rotordynamical model for a magnetic bearing supported rotor system, including auxiliary bearing effects. A finite element model for a foil bearing has been developed. Additional studies of rotor/bearing/housing dynamics are currently being performed as are studies of the effects of sideloading on auxiliary bearing rotordynamics using the magnetic bearing supported rotor model.

Association between TLR2 and TLR4 Gene Polymorphisms and the Susceptibility to Inflammatory Bowel Disease: A Meta-Analysis.

PubMed

Cheng, Yang; Zhu, Yun; Huang, Xiuping; Zhang, Wei; Han, Zelong; Liu, Side

2015-01-01

The associations between toll-like receptor 2 (TLR2) and toll-like receptor 4(TLR4) polymorphisms and inflammatory bowel disease (IBD) susceptibility remain controversial. A meta-analysis was performed to assess these associations. A systematic search was performed to identify all relevant studies relating TLR2 and TLR4 polymorphisms and IBD susceptibility. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Subgroup analyses were performed by ethnicity and publication quality. Thirty-eight eligible studies, assessing 10970 cases and 7061 controls were included. No TLR2 Arg677Trp polymorphism was found. No significant association was observed between TLR2 Arg753Gln polymorphism and Crohn's disease (CD) or ulcerative colitis (UC) in all genetic models. Interestingly, TLR4 Asp299Gly polymorphism was significantly associated with increased risk of CD and UC in all genetic models, except for the additive one in CD. In addition, a statistically significant association between TLR4 Asp299Gly polymorphism and IBD was observed among high quality studies evaluating Caucasians, but not Asians. Associations between TLR4 Thr399Ile polymorphisms and CD risk were found only in the allele and dominant models. The TLR4 Thr399Ile polymorphism was associated with UC risk in pooled results as well as subgroup analysis of high quality publications assessing Caucasians, in allele and dominant models. The meta-analysis provides evidence that TLR2 Arg753Gln is not associated with CD and UC susceptibility in Asians; TLR4 Asp299Gly is associated with CD and UC susceptibility in Caucasians, but not Asians. TLR4 Thr399Ile may be associated with IBD susceptibility in Caucasians only. Additional well-powered studies of Asp299Gly and other TLR4 variants are warranted.

Overview of the CLIC detector and its physics potential

NASA Astrophysics Data System (ADS)

Ström, Rickard

2017-12-01

The CLIC detector and physics study (CLICdp) is an international collaboration that investigates the physics potential of the Compact Linear Collider (CLIC). CLIC is a high-energy electron-positron collider under development, aiming for centre-of-mass energies from a few hundred GeV to 3 TeV. In addition to physics studies based on full Monte Carlo simulations of signal and background processes, CLICdp performs cuttingedge hardware R&D. In this contribution CLICdp will present recent results from physics prospect studies, emphasising Higgs studies. Additionally the new CLIC detector model and the recently updated CLIC baseline staging scenario will be presented.

On the additive and dominant variance and covariance of individuals within the genomic selection scope.

PubMed

Vitezica, Zulma G; Varona, Luis; Legarra, Andres

2013-12-01

Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or "breeding" values of individuals are generated by substitution effects, which involve both "biological" additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the "genotypic" value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts.

CRAC2 model description

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ritchie, L.T.; Alpert, D.J.; Burke, R.P.

1984-03-01

The CRAC2 computer code is a revised version of CRAC (Calculation of Reactor Accident Consequences) which was developed for the Reactor Safety Study. This document provides an overview of the CRAC2 code and a description of each of the models used. Significant improvements incorporated into CRAC2 include an improved weather sequence sampling technique, a new evacuation model, and new output capabilities. In addition, refinements have been made to the atmospheric transport and deposition model. Details of the modeling differences between CRAC2 and CRAC are emphasized in the model descriptions.

Uncertainty in tsunami sediment transport modeling

USGS Publications Warehouse

Jaffe, Bruce E.; Goto, Kazuhisa; Sugawara, Daisuke; Gelfenbaum, Guy R.; La Selle, SeanPaul M.

2016-01-01

Erosion and deposition from tsunamis record information about tsunami hydrodynamics and size that can be interpreted to improve tsunami hazard assessment. We explore sources and methods for quantifying uncertainty in tsunami sediment transport modeling. Uncertainty varies with tsunami, study site, available input data, sediment grain size, and model. Although uncertainty has the potential to be large, published case studies indicate that both forward and inverse tsunami sediment transport models perform well enough to be useful for deciphering tsunami characteristics, including size, from deposits. New techniques for quantifying uncertainty, such as Ensemble Kalman Filtering inversion, and more rigorous reporting of uncertainties will advance the science of tsunami sediment transport modeling. Uncertainty may be decreased with additional laboratory studies that increase our understanding of the semi-empirical parameters and physics of tsunami sediment transport, standardized benchmark tests to assess model performance, and development of hybrid modeling approaches to exploit the strengths of forward and inverse models.

Accelerated cure of phenol-formaldehyde by the addition of cure accelerators : studies with model compounds

Treesearch

Linda F. Lorenz; Anthony C. Conner

2000-01-01

Fast curing phenol-formaldehyde (PF) resins could potentially allow wood to be bonded at higher moisture contents and at lower press temperatures than those currently used commercially. Recent reports in the literature have shown that the addition of esters, lactones, or organic carbonates increased the curing rate of PF resins. Several mechanisms have been proposed to...

Low-molecular-weight model study of peroxide cross-linking of ethylene-propylene-diene rubber using gas chromatography and mass spectrometry II. Addition and combination reactions.

PubMed

Peters, R; van Duin, M; Tonoli, D; Kwakkenbos, G; Mengerink, Y; van Benthem, R A T M; de Koster, C G; Schoenmakers, P J; van der Wal, Sj

2008-08-08

The dicumyl-peroxide-initiated addition and combination reactions of mixtures of alkanes (n-octane, n-decane) and alkenes [5,6-dihydrodicyclopentadiene (DCPDH), 5-ethylidene-2-norbornane (ENBH) and 5-vinylidene-2-norbornane (VNBH)] were studied to mimic the peroxide cross-linking reactions of terpolymerised ethylene, propylene and a diene monomer (EPDM). The reaction products of the mixtures were separated by both gas chromatography (GC) and comprehensive two-dimensional gas chromatography (GCxGC). The separated compounds were identified from their mass spectra and their GC and GCxGC elution pattern. Quantification of the various alkyl/alkyl, alkyl/allyl and allyl/allyl combination products shows that allylic-radicals comprise approximately 60% of the substrate radicals formed. The total concentration of the products formed by combination is found to be independent of the concentration and the type of alkene. The total concentration of the products formed by addition to the alkene increases with increasing concentration of alkene. In addition, the total concentration of the formed addition products depends strongly on the type of the alkene used, viz. VNBH>ENBH approximately DCPDH, which is a consequence of differences in steric hindrance of the unsaturation. The peroxide curing efficiency, defined as the number of moles of cross-linked products formed per mol of peroxide, is 173% using 9% (w/w) 5-vinylidene-2-norbornane (VNBH). This indicates that the addition reaction is recurrent. All these findings are consistent with experimental studies on peroxide curing of EPDM rubber. In addition, the present results provide more-detailed structural information, increasing the understanding of the mechanism of peroxide curing of EPDM. The described approach to use low-molecular-weight model compounds followed by GC-mass spectrometry (MS) and GCxGC-MS analysis is proven to be a very powerful tool to study the cross-linking of EPDM.

Aging of nickel added to soils as predicted by soil pH and time.

PubMed

Ma, Yibing; Lombi, Enzo; McLaughlin, Mike J; Oliver, Ian W; Nolan, Annette L; Oorts, Koen; Smolders, Erik

2013-08-01

Although aging processes are important in risk assessment for metals in soils, the aging of Ni added to soils has not been studied in detail. In this study, after addition of water soluble Ni to soils, the changes over time in isotopic exchangeability, total concentrations and free Ni(2+) activity in soil pore water, were investigated in 16 European soils incubated outdoors for 18 months. The results showed that after Ni addition, concentrations of Ni in soil pore water and isotopic exchangeability of Ni in soils initially decreased rapidly. This phase was followed by further decreases in the parameters measured but these occurred at slower rates. Increasing soil pH increased the rate and extent of aging reactions. Semi-mechanistic models, based on Ni precipitation/nucleation on soil surfaces and micropore diffusion, were developed and calibrated. The initial fast processes, which were attributed to precipitation/nucleation, occurred over a short time (e.g. 1h), afterwards the slow processes were most likely controlled by micropore diffusion processes. The models were validated by comparing predicted and measured Ni aging in three additional, widely differing soils aged outdoors for periods up to 15 months in different conditions. These models could be used to scale ecotoxicological data generated in short-term studies to longer aging times. Copyright © 2013 Elsevier Ltd. All rights reserved.

Experimental and thermodynamic study of Co-Fe and Mn-Fe based mixed metal oxides for thermochemical energy storage application

NASA Astrophysics Data System (ADS)

André, Laurie; Abanades, Stéphane; Cassayre, Laurent

2017-06-01

Metal oxides are potential materials for thermochemical heat storage, and among them, cobalt oxide and manganese oxide are attracting attention. Furthermore, studies on mixed oxides are ongoing, as the synthesis of mixed oxides could be a way to answer the drawbacks of pure metal oxides, such as slow reaction kinetics, loss-in-capacity over cycles or sintering, selected for thermochemical heat storage application. The addition of iron oxide is under investigation and the obtained results are presented. This work proposes a comparison of thermodynamic modelling with experimental data in order to identify the impact of iron oxide addition to cobalt oxide and manganese oxide. Fe addition decreased the redox activity and energy storage capacity of Co3O4, whereas the cycling stability of Mn2O3 was significantly improved with added Fe amounts above 20 mol% while the energy storage capacity was unchanged. The thermodynamic modelling method to predict the behavior of the Mn-Fe-O and Co-Fe-O systems was validated, and the possibility to identify other mixed oxides becomes conceivable, by enabling the selection of transition metals additives for metal oxides destined for thermochemical energy storage applications.

Influence of polymer additive on flow past a hydrofoil: A numerical study

NASA Astrophysics Data System (ADS)

Xiong, Yongliang; Peng, Sai; Yang, Dan; Duan, Juan; Wang, Limin

2018-01-01

Flows of dilute polymer solutions past a hydrofoil (NACA0012) are examined by direct numerical simulation to investigate the modification of the wake pattern due to the addition of polymer. The influence of polymer additive is modeled by the FENE-P model in order to simulate a non-linear modulus of elasticity and a finite extendibility of the polymer macromolecules. Simulations were carried out at a Reynolds number of 1000 with the angle of attack varying from 0° to 20°. The results show that the influence of polymer on the flow behavior of the flow past a hydrofoil exhibits different flow regimes. In general, the addition of polymer modifies the wake patterns for all angles of attack in this study. Consequently, both drag and lift forces are changed as the Weissenberg number increases while the drag of the hydrofoil is enhanced at small angles of attack and reduced at large angles of attack. As the Weissenberg number increases, two attached recirculation bubbles or two columns of shedding vortices downstream tend to be symmetric, and the polymer tends to make the flow less sensitive to the variation of the angle of attack.

Nitrogen and Sulfur Deposition Effects on Forest Biogeochemical Processes.

NASA Astrophysics Data System (ADS)

Goodale, C. L.

2014-12-01

Chronic atmospheric deposition of nitrogen and sulfur have widely ranging biogeochemical consequences in terrestrial ecosystems. Both N and S deposition can affect plant growth, decomposition, and nitrous oxide production, with sometimes synergistic and sometimes contradictory responses; yet their separate effects are rarely isolated and their interactive biogeochemical impacts are often overlooked. For example, S deposition and consequent acidification and mortality may negate stimulation of plant growth induced by N deposition; decomposition can be slowed by both N and S deposition, though through different mechanisms; and N2O production may be stimulated directly by N and indirectly by S amendments. Recent advances in conceptual models and whole-ecosystem experiments provide novel means for disentangling the impacts of N and S in terrestrial ecosystems. Results from a new whole-ecosystem N x S- addition experiment will be presented in detail, examining differential response of tree and soil carbon storage to N and S additions. These results combine with observations from a broad array of long-term N addition studies, atmospheric deposition gradients, stable isotope tracer studies, and model analyses to inform the magnitude, controls, and stability of ecosystem C storage in response to N and S addition.

Process simulation and comparison of biological conversion of syngas and hydrogen in biogas plants

NASA Astrophysics Data System (ADS)

Awais Salman, Chaudhary; Schwede, Sebastian; Thorin, Eva; Yan, Jinyue

2017-11-01

Organic waste is a good source of clean energy. However, different fractions of waste have to be utilized efficiently. One way is to find pathways to convert waste into useful products via various available processes (gasification, pyrolysis anaerobic digestion, etc.) and integrate them to increase the combined efficiency of the process. The syngas and hydrogen produced from the thermal conversion of biomass can be upgraded to biomethane via biological methanation. The current study presents the simulation model to predict the amount of biomethane produced by injecting the hydrogen and syngas. Hydrogen injection is modelled both in-situ and ex-situ while for syngas solely the ex-situ case has been studied. The results showed that 85% of the hydrogen conversion was achieved for the ex-situ reactor while 81% conversion rate was achieved for the in-situ reactor. The syngas could be converted completely in the bio-reactor. However, the addition of syngas resulted in an increase of carbon dioxide. Simulation of biomethanation of gas addition showed a biomethane concentration of 87% while for hydrogen addition an increase of 74% and 80% for in-situ and ex-situ addition respectively.

The cost of an additional disability-free life year for older Americans: 1992-2005.

PubMed

Cai, Liming

2013-02-01

To estimate the cost of an additional disability-free life year for older Americans in 1992-2005. This study used 1992-2005 Medicare Current Beneficiary Survey, a longitudinal survey of Medicare beneficiaries with a rotating panel design. This analysis used multistate life table model to estimate probabilities of transition among a discrete set of health states (nondisabled, disabled, and dead) for two panels of older Americans in 1992 and 2002. Health spending incurred between annual health interviews was estimated by a generalized linear mixed model. Health status, including death, was simulated for each member of the panel using these transition probabilities; the associated health spending was cross-walked to the simulated health changes. Disability-free life expectancy (DFLE) increased significantly more than life expectancy during the study period. Assuming that 50 percent of the gains in DFLE between 1992 and 2005 were attributable to increases in spending, the average discounted cost per additional disability-free life year was $71,000. There were small differences between gender and racial/ethnic groups. The cost of an additional disability-free life year was substantially below previous estimates based on mortality trends alone. © Health Research and Educational Trust.

An electrical circuit model for additive-modified SnO2 ceramics

NASA Astrophysics Data System (ADS)

Karami Horastani, Zahra; Alaei, Reza; Karami, Amirhossein

2018-05-01

In this paper an electrical circuit model for additive-modified metal oxide ceramics based on their physical structures and electrical resistivities is presented. The model predicts resistance of the sample at different additive concentrations and different temperatures. To evaluate the model two types of composite ceramics, SWCNT/SnO2 with SWCNT concentrations of 0.3, 0.6, 1.2, 2.4 and 3.8%wt, and Ag/SnO2 with Ag concentrations of 0.3, 0.5, 0.8 and 1.5%wt, were prepared and their electrical resistances versus temperature were experimentally measured. It is shown that the experimental data are in good agreement with the results obtained from the model. The proposed model can be used in the design process of ceramic-based gas sensors, and it also clarifies the role of additive in gas sensing process of additive-modified metal oxide gas sensors. Furthermore the model can be used in the system level modeling of designs in which these sensors are also present.

Updated one-dimensional hydraulic model of the Kootenai River, Idaho-A supplement to Scientific Investigations Report 2005-5110

USGS Publications Warehouse

Czuba, Christiana R.; Barton, Gary J.

2011-01-01

The Kootenai Tribe of Idaho, in cooperation with local, State, Federal, and Canadian agency co-managers and scientists, is assessing the feasibility of a Kootenai River habitat restoration project in Boundary County, Idaho. The restoration project is focused on recovery of the endangered Kootenai River white sturgeon (Acipenser transmontanus) population, and simultaneously targets habitat-based recovery of other native river biota. River restoration is a complex undertaking that requires a thorough understanding of the river and floodplain landscape prior to restoration efforts. To assist in evaluating the feasibility of this endeavor, the U.S. Geological Survey developed an updated one-dimensional hydraulic model of the Kootenai River in Idaho between river miles (RMs) 105.6 and 171.9 to characterize the current hydraulic conditions. A previously calibrated model of the study area, based on channel geometry data collected during 2002 and 2003, was the basis for this updated model. New high-resolution bathymetric surveys conducted in the study reach between RMs 138 and 161.4 provided additional detail of channel morphology. A light detection and ranging (LIDAR) survey was flown in the Kootenai River valley in 2005 between RMs 105.6 and 159.5 to characterize the floodplain topography. Six temporary gaging stations installed in 2006-08 between RMs 154.1 and 161.2, combined with five permanent gaging stations in the study reach, provided discharge and water-surface elevations for model calibration and verification. Measured discharges ranging from about 4,800 to 63,000 cubic feet per second (ft3/s) were simulated for calibration events, and calibrated water-surface elevations ranged from about 1,745 to 1,820 feet (ft) throughout the extent of the model. Calibration was considered acceptable when the simulated and measured water-surface elevations at gaging stations differed by less than (+/-)0.15 ft. Model verification consisted of simulating 10 additional events with measured discharges ranging from about 4,900 to 52,000 ft3/s, and comparing simulated and measured water-surface elevations at gaging stations. Average water-surface-elevation error in the verification simulations was 0.05 ft, with the error ranging from -1.17 to 0.94 ft over the range of events and gaging stations. Additional verification included a graphical comparison of measured average velocities that range from 1.0 to 6.2 feet per second to simulated velocities at four sites within the study reach for measured discharges ranging from about 7,400 to 46,600 ft3/s. The availability of high-resolution bathymetric and LIDAR data, along with the additional gaging stations in the study reach, allowed for more detail to be added to the model and a more thorough calibration, sensitivity, and verification analysis to be conducted. Model resolution and performance is most improved between RMs 140 and 160, which includes the 18.3-mile reach of the Kootenai River white sturgeon critical habitat.

Further Studies of Aerodynamic Loads at Spin Entry

DTIC Science & Technology

1977-06-30

the model and the loads on the model for a research coafiguration having certain essential features of a modern fighter-bomber aircraft, since no such...percent at the tip. The model is geometrically similar to that described in reference 3 but approximately 2.4 times larger. The NASA model is designed to...measurements turned out to be extremely time consuming. Even though the V/STOL tunnel staff granted three additional days over the 10 originally scheduled for

Modeling of Micro Deval abrasion loss based on some rock properties

NASA Astrophysics Data System (ADS)

Capik, Mehmet; Yilmaz, Ali Osman

2017-10-01

Aggregate is one of the most widely used construction material. The quality of the aggregate is determined using some testing methods. Among these methods, the Micro Deval Abrasion Loss (MDAL) test is commonly used for the determination of the quality and the abrasion resistance of aggregate. The main objective of this study is to develop models for the prediction of MDAL from rock properties, including uniaxial compressive strength, Brazilian tensile strength, point load index, Schmidt rebound hardness, apparent porosity, void ratio Cerchar abrasivity index and Bohme abrasion test are examined. Additionally, the MDAL is modeled using simple regression analysis and multiple linear regression analysis based on the rock properties. The study shows that the MDAL decreases with the increase of uniaxial compressive strength, Brazilian tensile strength, point load index, Schmidt rebound hardness and Cerchar abrasivity index. It is also concluded that the MDAL increases with the increase of apparent porosity, void ratio and Bohme abrasion test. The modeling results show that the models based on Bohme abrasion test and L type Schmidt rebound hardness give the better forecasting performances for the MDAL. More models, including the uniaxial compressive strength, the apparent porosity and Cerchar abrasivity index, are developed for the rapid estimation of the MDAL of the rocks. The developed models were verified by statistical tests. Additionally, it can be stated that the proposed models can be used as a forecasting for aggregate quality.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

2011-01-01

Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118

A Potential Role of the Curry Spice Curcumin in Alzheimer’s Disease

PubMed Central

Ringman, John M.; Frautschy, Sally A.; Cole, Gregory M.; Masterman, Donna L.; Cummings, Jeffrey L.

2005-01-01

There is substantial in-vitro data indicating that curcumin has antioxidant, anti-inflammatory, and anti-amyloid activity. In addition, studies in animal models of Alzheimer’s disease (AD) indicate a direct effect of curcumin in decreasing the amyloid pathology of AD. As the widespread use of curcumin as a food additive and relatively small short-term studies in humans suggest safety, curcumin is a promising agent in the treatment and/or prevention of AD. Nonetheless, important information regarding curcumin bioavailability, safety and tolerability, particularly in an elderly population is lacking. We are therefore performing a study of curcumin in patients with AD to gather this information in addition to data on the effect of curcumin on biomarkers of AD pathology. PMID:15974909

Leading for Change: How Leadership Style Impacts Teachers' Experience

ERIC Educational Resources Information Center

Procek, Cara

2012-01-01

This research study explored how one middle school in a suburban New Hampshire town translates existing models of leadership into practice and how teachers experience these differences in practice. The research examined how school leaders balance formal and cultural models of leadership to affect change on a day-to-day level. In addition, the…

Dynamics of buckbrush populations under simulated forest restoration alternatives

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...

Dynamics of buckbrush populations under simulated forest restoration alternatives (P-53)

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...

Do Teacher-Child Relationship and Friendship Quality Matter for Children's School Engagement and Academic Skills?

ERIC Educational Resources Information Center

Hosan, Naheed E.; Hoglund, Wendy

2017-01-01

This study examined three competing models assessing the directional associations between the quality of children's relationships with teachers and friends (i.e., closeness and conflict) and their emotional and behavioral school engagement (i.e., the relationship-driven, engagement-driven, and transactional models). The additive contributions of…

Invariance of an Extended Technology Acceptance Model Across Gender and Age Group

ERIC Educational Resources Information Center

Ahmad, Tunku Badariah Tunku; Madarsha, Kamal Basha; Zainuddin, Ahmad Marzuki; Ismail, Nik Ahmad Hisham; Khairani, Ahmad Zamri; Nordin, Mohamad Sahari

2011-01-01

In this study, we examined the likelihood of a TAME (extended technology acceptance model), in which the interrelationships among computer self-efficacy, perceived usefulness, intention to use and self-reported use of computer-mediated technology were tested. In addition, the gender- and age-invariant of its causal structure were evaluated. The…

Defining and Comparing the Reading Comprehension Construct: A Cognitive-Psychometric Modeling Approach

ERIC Educational Resources Information Center

Svetina, Dubravka; Gorin, Joanna S.; Tatsuoka, Kikumi K.

2011-01-01

As a construct definition, the current study develops a cognitive model describing the knowledge, skills, and abilities measured by critical reading test items on a high-stakes assessment used for selection decisions in the United States. Additionally, in order to establish generalizability of the construct meaning to other similarly structured…

Probing for the Multiplicative Term in Modern Expectancy-Value Theory: A Latent Interaction Modeling Study

ERIC Educational Resources Information Center

Trautwein, Ulrich; Marsh, Herbert W.; Nagengast, Benjamin; Ludtke, Oliver; Nagy, Gabriel; Jonkmann, Kathrin

2012-01-01

In modern expectancy-value theory (EVT) in educational psychology, expectancy and value beliefs additively predict performance, persistence, and task choice. In contrast to earlier formulations of EVT, the multiplicative term Expectancy x Value in regression-type models typically plays no major role in educational psychology. The present study…

Structural Equation Modeling in Assessing Students' Understanding of the State Changes of Matter

ERIC Educational Resources Information Center

Stamovlasis, Dimitrios; Tsitsipis, Georgios; Papageorgiou, George

2012-01-01

In this study, structural equation modeling (SEM) is applied to an instrument assessing students' understanding of the particulate nature of matter, the collective properties and physical changes, such as melting, evaporation, boiling and condensation. The structural relationships among particular groups of items were investigated. In addition,…

Virtual Transgenics: Using a Molecular Biology Simulation to Impact Student Academic Achievement and Attitudes

ERIC Educational Resources Information Center

Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva

2012-01-01

The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach.…

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

PubMed

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

RTEL1 and TERT polymorphisms are associated with astrocytoma risk in the Chinese Han population.

PubMed

Jin, Tian-Bo; Zhang, Jia-Yi; Li, Gang; Du, Shu-Li; Geng, Ting-Ting; Gao, Jing; Liu, Qian-Ping; Gao, Guo-Dong; Kang, Long-Li; Chen, Chao; Li, Shan-Qu

2013-12-01

Common variants of multiple genes play a role in glioma onset. However, research related to astrocytoma, the most common primary brain neoplasm, is rare. In this study, we chose 21 tagging SNPs (tSNPs), previously reported to be associated with glioma risk in a Chinese case-control study from Xi'an, China, and identified their contributions to astrocytoma susceptibility. We found an association with astrocytoma susceptibility for two tSNPs (rs6010620 and rs2853676) in two different genes: regulator of telomere elongation helicase 1 (RTEL1) and telomerase reverse transcriptase (TERT), respectively. We confirmed our results using recessive, dominant, and additive models. In the recessive model, we found two tSNPs (rs2297440 and rs6010620) associated with increased astrocytoma risk. In the dominant model, we found that rs2853676 was associated with increased astrocytoma risk. In the additive model, all three tSNPs (rs2297440, rs2853676, and rs6010620) were associated with increased astrocytoma risk. Our results demonstrate, for the first time, the potential roles of RTEL1 and TERT in astrocytoma development.

Computational Process Modeling for Additive Manufacturing

NASA Technical Reports Server (NTRS)

Bagg, Stacey; Zhang, Wei

2014-01-01

Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

The Bridging Integrator 1 Gene Polymorphism rs744373 and the Risk of Alzheimer's Disease in Caucasian and Asian Populations: An Updated Meta-Analysis.

PubMed

Zhu, Ruixia; Liu, Xu; He, Zhiyi

2017-03-01

Recent genome-wide association studies have identified an association between the bridging integrator 1 gene (BIN1) rs744373 polymorphism and late-onset Alzheimer's disease (LOAD) in individuals of European ancestry. Additionally, a number of studies have focused on the association between rs744373 and Alzheimer's disease in Caucasian and East Asian populations. However, these results remain inconclusive because of the relatively small sample sizes investigated. Here, we reevaluated this association using samples from seven articles including 22 independent studies comprising 11,832 LOAD patients and 18,133 controls identified by searching PubMed, MEDLINE, and AlzGene databases up to December 2015. We observed no significant heterogeneity between Asian and Caucasian populations. Additive, dominant, and recessive models revealed a significant association between rs744373 and LOAD in the pooled population, while subgroup analysis also identified significant findings in the East Asian population under the additive model (odds ratio (OR) = 1.10, 95 % confidence interval (CI) 1.02-1.19, P = 0.01) and dominant model (OR = 1.13, 95 % CI 1.03-1.25, P = 0.01), but not under the recessive model. The current meta-analysis further supports previous findings that the rs744373 polymorphism may be associated with LOAD risk in Caucasian and Asian populations. To our knowledge, this is the first large meta-analysis to investigate the association between the rs744373 polymorphism and LOAD in East Asian, American, and European populations.